US20120047448A1 - System and method for social browsing using aggregated profiles - Google Patents

System and method for social browsing using aggregated profiles Download PDF

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US20120047448A1
US20120047448A1 US12/769,802 US76980210A US2012047448A1 US 20120047448 A1 US20120047448 A1 US 20120047448A1 US 76980210 A US76980210 A US 76980210A US 2012047448 A1 US2012047448 A1 US 2012047448A1
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social
crowd
location
user
locations
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US12/769,802
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Christopher M. Amidon
Scott Curtis
Steven L. Petersen
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Waldeck Technology LLC
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Waldeck Technology LLC
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Priority to US12/769,802 priority patent/US20120047448A1/en
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    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/28Databases characterised by their database models, e.g. relational or object models
    • G06F16/284Relational databases
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce, e.g. shopping or e-commerce
    • G06Q30/02Marketing, e.g. market research and analysis, surveying, promotions, advertising, buyer profiling, customer management or rewards; Price estimation or determination
    • G06Q30/0202Market predictions or demand forecasting
    • G06Q30/0204Market segmentation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/01Social networking
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L51/00Arrangements for user-to-user messaging in packet-switching networks, e.g. e-mail or instant messages
    • H04L51/32Messaging within social networks
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W12/00Security arrangements, e.g. access security or fraud detection; Authentication, e.g. verifying user identity or authorisation; Protecting privacy or anonymity ; Protecting confidentiality; Key management; Integrity; Mobile application security; Using identity modules; Secure pairing of devices; Context aware security; Lawful interception
    • H04W12/02Protecting privacy or anonymity, e.g. protecting personally identifiable information [PII]
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W4/00Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02Services making use of location information
    • H04W4/029Location-based management or tracking services
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATION NETWORKS
    • H04W8/00Network data management
    • H04W8/02Processing of mobility data, e.g. registration information at HLR [Home Location Register] or VLR [Visitor Location Register]; Transfer of mobility data, e.g. between HLR, VLR or external networks
    • H04W8/08Mobility data transfer
    • H04W8/16Mobility data transfer selectively restricting mobility data tracking

Abstract

Systems and methods are disclosed for providing social crowd data for a number of social locations. In one embodiment, a social browsing system processes social crowd requests using social locations collected for users over time. In one embodiment, upon receiving a social crowd request, for each of one or more social locations identified for the social crowd request, the social browsing system identifies a social crowd for the social location. Optionally, the social crowds may be filtered. Social crowd data is generated for the social locations based on user profiles of the users in the corresponding social crowds. In one embodiment, the social crowd data is returned to a user device of a requesting user. In another embodiment, the social browsing system visualizes the social crowd data and returns the visualized social crowd data to the user device of the requesting user for presentation to the requesting user.

Description

    RELATED APPLICATIONS
  • This application claims the benefit of provisional patent application Ser. No. 61/173,625, filed Apr. 29, 2009, the disclosure of which is hereby incorporated herein by reference in its entirety.
  • FIELD OF THE DISCLOSURE
  • The present disclosure relates to generating social crowd data for social crowds identified for a number of social locations.
  • BACKGROUND
  • Social networking websites such as Facebook®, MySpace®, and LinkedIN® have become prolific in today's society. Further, other types of applications such as gaming applications have started to incorporate social networking features. A single user may typically participate in multiple social networks and multiple applications or services having social networking features in a given day or week. For example, it is common for a user to frequently participate on the Facebook® website, chat using one or more Instant Messaging (IM) applications, play an online game having a social networking feature such as chatting, etc. Additionally, it is becoming increasingly common for users to “check in” at online media locations or activities (websites, television shows, movies, chat sessions, etc.) through the use of widgets or applications associated with sites or services like Facebook®. Because a user typically has many such opportunities to engage in social networking activities, there is a need for a system and method that enable a user to quickly and easily obtain information about other users that currently are using, have historically used, or are expected to use such applications or services. Based on this information, the user can quickly determine which application or service that he or she would like to use at that time.
  • SUMMARY
  • Systems and methods are disclosed for providing social crowd data for a number of social locations. A social location is a service or application in which users participate. Preferably, a social location is a social networking service or application or a service or application that has a social networking feature. In one embodiment, a social browsing system collects social locations for a number of users over time. Using the collected social locations for the users, the social browsing system processes social crowd requests. In one embodiment, upon receiving a social crowd request from a user device of a requesting user, for each of one or more social locations identified for the social crowd request, the social browsing system identifies a social crowd for the social location. In one embodiment, the social crowd for the social location includes users currently at the social location. In another embodiment, the social crowd for the social location includes users historically at the social location. In yet another embodiment, the social crowd for the social location includes both users currently and historically at the social location. Optionally, the social crowds identified for the one or more social locations identified for the social crowd request may be filtered using one or more system-defined or user-defined filtering criteria. The social browsing system then generates social crowd data for the social locations based on user profiles of the users in the corresponding social crowds. In one embodiment, for each social location, the social crowd data includes an affinity between the requesting user and the social crowd identified for the social location. In addition, for each social location, the social crowd data may include a number of users in the social crowd identified for the social location. In one embodiment, the social crowd data is returned to the user device of the requesting user where the social crowd data may be visualized and presented to the requesting user. In another embodiment, the social browsing system visualizes the social crowd data and returns the visualized social crowd data to the user device of the requesting user for presentation to the requesting user.
  • In one embodiment, the social browsing system returns the social crowd data to the user device of the requesting user. A social browsing client operating on the user device of the requesting user then provides a Graphical User Interface (GUI) that visualizes the social crowd data received from the social browsing system. In one embodiment, the GUI includes an icon or other representation for each of at least a subset of the social locations identified for the social crowd request. For each social location of those represented in the GUI, a visual characteristic of the corresponding representation in the GUI is controlled to be indicative of the affinity between the requesting user and the social crowd identified for the social location. In addition, another visual characteristic of the corresponding representation in the GUI may be controlled to be indicative of the number of users in the social crowd identified for the social location.
  • In another embodiment, the social browsing system provides a web interface, where the user device of the requesting user accesses the social browsing system via a web browser. In this embodiment, the social browsing system processes the social crowd data generated in response to the social crowd request from the requesting user to provide a web page or similar web content that visualizes the social crowd data. The social browsing system then provides the web page or similar web content to the user device of the requesting user for rendering via the web browser of the user device. For each of at least a subset of the social locations in the social crowd request, a visual characteristic of a corresponding representation in the web page or similar web content is controlled to be indicative of the affinity between the requesting user and the social crowd identified for the social location. In addition, another visual characteristic of the corresponding representation may be controlled to be indicative of the number of users in the social crowd identified for the social location.
  • In another embodiment, a social browsing system collects social locations for a number of users over time. Using the collected social locations for the users, the social browsing system processes social crowd requests for predicted social crowd data. In one embodiment, upon receiving a social crowd request from a user device of a requesting user, for each of one or more social locations identified for the social crowd request, the social browsing system identifies a number of social crowds for the social location over a defined historical time period. Optionally, the social crowds identified for the one or more social locations identified for the social crowd request may be filtered using one or more system-defined or user-defined filtering criteria. For each social location identified for the social crowd request, the social browsing system obtains social crowd data for the social crowds identified for the social location over the historical time period, determines a trend in the social crowd data, and generates predicted social crowd data for the social location based on the trend. In one embodiment, the predicted social crowd data is returned to the user device of the requesting user where the predicted social crowd data may be visualized and presented to the requesting user. In another embodiment, the social browsing system visualizes the predicted social crowd data and returns the visualized predicted social crowd data to the user device of the requesting user for presentation to the requesting user.
  • Those skilled in the art will appreciate the scope of the present disclosure and realize additional aspects thereof after reading the following detailed description of the preferred embodiments in association with the accompanying drawing figures.
  • BRIEF DESCRIPTION OF THE DRAWING FIGURES
  • The accompanying drawing figures incorporated in and forming a part of this specification illustrate several aspects of the disclosure, and together with the description serve to explain the principles of the disclosure.
  • FIG. 1 illustrates a system for collecting social locations of users and providing social crowd data for social locations based on user profiles of the users according to one embodiment of the present disclosure;
  • FIG. 2 illustrates the operation of the social browsing system of FIG. 1 to collect social locations of users over time from one or more web-based social locations according to one embodiment of the present disclosure;
  • FIG. 3 illustrates the operation of the social browsing system of FIG. 1 to collect social locations of users over time from user devices of the users according to one embodiment of the present disclosure;
  • FIG. 4 illustrates the operation of the social browsing system of FIG. 1 to process a social crowd request according to one embodiment of the present disclosure;
  • FIG. 5 is a flow chart illustrating a process for generating social crowd data for a number of social locations in response to a social crowd request according to one embodiment of the present disclosure;
  • FIG. 6 illustrates an exemplary Graphical User Interface (GUI) for presenting social crowd data to a requesting user according to one embodiment of the present disclosure;
  • FIG. 7 illustrates an alternative embodiment of the system of FIG. 1 wherein the social browsing system is incorporated into a social networking system;
  • FIG. 8 illustrates another alternative embodiment of the system of FIG. 1 wherein the social browsing system collects social locations of the users via a third-party presence system according to one embodiment of the present disclosure;
  • FIG. 9 is a block diagram of the social browsing system of FIG. 1 according to one embodiment of the present disclosure;
  • FIG. 10 is a block diagram of the social networking system including the social browsing system of FIG. 7 according to one embodiment of the present disclosure; and
  • FIG. 11 is a block diagram of one of the user devices of FIGS. 1 and 7 according to one embodiment of the present disclosure.
  • DETAILED DESCRIPTION
  • The embodiments set forth below represent the necessary information to enable those skilled in the art to practice the embodiments and illustrate the best mode of practicing the embodiments. Upon reading the following description in light of the accompanying drawing figures, those skilled in the art will understand the concepts of the disclosure and will recognize applications of these concepts not particularly addressed herein. It should be understood that these concepts and applications fall within the scope of the disclosure and the accompanying claims.
  • FIG. 1 illustrates a system 10 for providing social crowd data for social locations according to one embodiment of the present disclosure. As used herein, a social crowd is a group of users that are currently at a social location, a group of users that were historically, or previously, at a social location during one or more defined historical periods of time, or a group of users that includes both users that are currently at a social location and users that were historically at the social location, depending on the particular implementation. As used herein, a social location is not a geographic location. Rather, a social location is a service or application in which users participate. Similarly, a social location of a user is a service or application with which the user is participating at a particular time. Preferably, the service or application identified as a social location is a social networking service or application, or a service or application that has a social networking feature. A social networking feature may be any type of feature that enables one user to interact with another user such as, for example, voice or text chatting or instant messaging, exchanging messages on a message board, sharing or exchanging media content (e.g., picture files, audio files, or video files), or the like. As a non-limiting example, a social location may be a social networking website (e.g., Facebook®, MySpace®, or LinkedIN®), a social networking application (e.g., AIM), a media sharing application (e.g., Picasa®, Flickr®), an online game (e.g., World of Warcraft®, online card game like those through Yahoo!® Games), a website, a service or application provided on a gaming console (e.g., in game chatting on PlayStation® 3), or an online media service (e.g., Netflix® online streaming movie service).
  • As illustrated in FIG. 1, the system 10 includes a social browsing system 12, one or more web-based social locations 14 (generally referred to herein as web-based social locations 14 or web-based social location 14), and a number of user devices 16-1 through 16-N (also generally referred to herein as user devices 16 or user device 16) having associated users 18-1 through 18-N (also generally referred to herein as users 18 or user 18). The social browsing system 12 is connected to the web-based social locations 14 and the user devices 16 via a network 20. The network 20 may be any type or combination of types of networks. In one embodiment, the network 20 is a distributed public network such as the Internet. Each of the social browsing system 12, the web-based social locations 14, and the user devices 16 is connected to the network 20 via a wired or wireless connection. The system 10 also includes an aggregate profile server 22.
  • In this embodiment, the social browsing system 12 is preferably implemented as a physical server or group of physical servers that operate in a collaborative manner for purposes of redundancy or load-sharing. The social browsing system 12 includes a social location collector 24, which is preferably implemented in software but is not limited thereto. In general, the social location collector 24 operates to collect social locations of the users 18 over time and store the social locations of the users 18 in a user record repository 26. In addition, the social location collector 24 may collect user activities performed by the users 18 at the social locations.
  • The user record repository 26 includes a user record for each of the users 18. More specifically, for each user 18, the user record repository 26 includes a corresponding user record that includes a historical record of the social locations at which the user 18 has been located in the past and, optionally, timestamps defining times (e.g., dates and, optionally, times of day) that the user 18 was at the social locations. The user record of the user 18 may also include a historical record of user activities reported for the user 18 along with timestamps defining times at which the user 18 was performing the user activities. When the social location collector 24 obtains a social location update for the user 18, the social location identified by the social location update and, optionally, a timestamp defining the time at which the user 18 was at the social location are stored in the user record of the user 18, and more specifically stored in the historical record of social locations maintained for the user 18. Likewise, when the social location collector 24 obtains a user activity update, or report of a user activity, for the user 18, the user activity and, optionally, a timestamp defining the time at which the user 18 was performing the user activity are stored in the user record of the user 18, and more specifically stored in the historical record of user activities maintained for the user 18. The user record of the user 18 may also include a user profile of the user 18, where the user profile of the user 18 includes number of interests of the user 18 which may be expressed as keywords (e.g., Politics, Fishing, NC State, or the like). The user record of the user 18 may also include one or more user settings defined by the user 18 such as, for example, one or more filtering criteria to be used to filter social crowds, as described below.
  • The social browsing system 12 also includes a request processor 28, which is also preferably implemented in software but is not limited thereto. In general, the request processor 28 operates to process social crowd requests from the users 18. While discussed in detail below, upon receiving a social crowd request from one of the users 18 (also referred to herein as the requesting user 18), the request processor 28 identifies a social crowd for each of a number of social locations identified for the social crowd request and generates social crowd data for the social locations based on user profiles of users in the social crowds identified for the social locations. Optionally, the social crowds identified for the social locations may be filtered using one or more system-defined filtering criteria and/or one or more user-defined filtering criteria prior to generating the social crowd data. In this embodiment, the social crowd data is returned to the user device 16 of the requesting user 18 where the social crowd data is visualized and presented to the requesting user 18. Alternatively, the request processor 28 may visualize the social crowd data to provide corresponding web content, and provide the web content to the user device 16 of the requesting user 18 for presentation to the requesting user 18 via a web browser.
  • The web-based social locations 14 are generally any type of web-based application or service. For example, the web-based social locations 14 may be social networking websites (e.g., Facebook®, MySpace®, or LinkedIN®), online games (e.g., World of Warcraft®), websites (e.g., CNN.com or CBS.com), web-based media content providers (e.g., Hulu or Netflix®), or the like. The web-based social locations 14 are preferably hosted by one or more physical servers (not shown). Each web-based social location 14 includes, in this embodiment, a reporting function 30, which is preferably implemented in software but is not limited thereto. The reporting function 30 generally operates to send social location updates to the social browsing system 12 for the users 18 when the users 18 are at (e.g., logged into) the web-based social location 14. More specifically, as discussed below in detail, at least some of the users 18 are registered with the web-based social location 14. When one of the users 18 logs into the web-based social location 14, the reporting function 30 notifies the social browsing system 12. In response, the social location collector 24 records the web-based social location 14 as the social location of the user 18 at that time. Note that the reporting function 30 may report logins to the social browsing system 12 as the logins occur (i.e., event-based reporting) or may report logins to the social browsing system 12 in batches (e.g., periodically). For batch reporting, the reporting function 30 preferably reports both the users 18 that have logged into the web-based social location 14 and times (e.g., dates and/or times of day) that those users 18 logged into the web-based social location 14. Also, as discussed below in detail, the reporting function 30 may also report user activities performed by the users 18 at the web-based social location 14 to the social browsing system 12.
  • The user devices 16 may be, for example, personal computers, notebook computers, tablet computers (e.g., Apple® iPad®), mobile smart phones (e.g., Apple® iPhone®), portable media players (e.g., Apple® iPod Touch®), gaming consoles (e.g., Xbox®, PS3®, or Wii®), portable gaming devices (e.g., PSP®), or the like. The user devices 16-1 through 16-N include corresponding reporting functions 32-1 through 32-N (also generally referred to herein as reporting functions 32 or reporting function 32) and social browsing clients 34-1 through 34-N (also generally referred to herein as social browsing clients 34 or social browsing client 34). Note that while only one reporting function 32 is illustrated for each of the user devices 16, each of the user devices 16 may include one or more reporting functions 32 depending on the particular implementation. The reporting functions 32 are preferably implemented in software, but are not limited thereto. Further, the reporting functions 32 are preferably implemented in or as plug-ins to applications on the user devices 16 that correspond to social locations in the system 10. However, the reporting functions 32 are not limited thereto. For example, the online game World of Warcraft® may be a social location, and the reporting functions 32 for the user devices 16 of users 18 who participate in World of Warcraft® may be implemented within or as plug-ins to World of Warcraft® client applications stored on and executed by the user devices 16 of those users 18. In a similar manner, the user devices 16 may include reporting functions 32 for other applications on the user devices 16 that correspond to social locations.
  • The reporting functions 32 generally operate to detect the social locations of the users 18 and report the social locations of the users 18 to the social browsing system 12. The reporting functions 32 may also report activities performed by the user 18 at the social locations to the social browsing system 12. Note that, in this embodiment, the reporting functions 32 are utilized in addition to the reporting function 30. For instance, the reporting functions 30 of the web-based social locations 14 report the social locations of the users 18 when the users 18 are at the web-based social locations 14 having the reporting functions 30. The reporting functions 32 of the user devices 16 may then operate to report the social locations of the users 18 when the users 18 are at social locations other than the web-based social locations 14 that include the reporting functions 30. It should also be noted that in alternative embodiments, the system 10 may include only the reporting functions 30 of the web-based social locations 14 or the reporting functions 32 of the user devices 16 rather than both. Further, while in this embodiment all of the user devices 16 have reporting functions 32, the present disclosure is not limited thereto. For example, only a subset of the user devices 16 may have reporting functions 32.
  • The social browsing clients 34-1 through 34-N are preferably implemented in software and include social crowd data visualization functions 36-1 through 36-N (also generally referred to herein as visualization functions 36 or visualization function 36). As discussed below in more detail, the social browsing clients 34 operate to request and obtain social crowd data for a number of social locations from the social browsing system 12. The visualization functions 36 then process the social crowd data to provide and display visualized social crowd data. For example, as discussed below in detail, in one embodiment, the visualization functions 36 present graphical representations of a number of social locations where one or more visual characteristics of the graphical representations are controlled to be indicative of the social crowd data for the corresponding social locations.
  • The aggregate profile server 22, in this embodiment, is a physical server or group of physical servers. As discussed below, in operation, the aggregate profile server 22 operates to combine the user profiles of the users 18 in a social crowd to provide an aggregate profile for the social crowd. The aggregate profile for the social crowd is then utilized by the social browsing system 12 to generate social crowd data for a social location for which the social crowd has been identified, as described below. It should be noted that while the aggregate profile server 22 is separate from the social browsing system 12 in this embodiment, the present disclosure is not limited thereto. In an alternative embodiment, the functionality of the aggregate profile server 22 is implemented in the social browsing system 12.
  • FIG. 2 illustrates the operation of the social browsing system 12 to collect social locations of the users 18 from the one or more web-based social locations 14 according to one embodiment of the present disclosure. As illustrated, the reporting function 30 of the web-based social location 14 detects a user login for one of the users 18 (step 100). For example, if the web-based social location 14 is a social networking website such as Facebook®, the user 18 may login using his username and password. Upon detecting the user login, the reporting function 30 reports the user login to the social browsing system 12 (step 102). In one embodiment, the user 18 is a registered user with the web-based social location 14, and has configured his account such that login events are to be reported to the social browsing system 12. Preferably, the configurations include a user identifier (ID) of the user 18 for the social browsing system 12 such that social locations reported for the user 18 from multiple web-based social locations 14 and the user device 16 of the user 18 are all linked to the same user ID. When reporting the login event to the social browsing system 12, the user 18 is preferably identified by a user ID assigned to the user 18 in the social browsing system 12. Alternatively, the user 18 may provide usernames or other identifiers for the user 18 at the web-based social locations 14 and a username or other identifier for the user 18 at the user device 16 to the social browsing system 12 such that the social location collector 24 can correlate social locations for the user 18 reported by the web-based social locations 14 and the user device 16 of the user 18.
  • Upon receiving the report of the user login of the user 18, the social location collector 24 of the social browsing system 12 stores the web-based social location 14 as the social location of the user 18 (step 104). For example, if the web-based social location 14 is a social networking website such as Facebook®, the social location collector 24 may store a predefined identifier for that social networking website (e.g., a URL of the social networking website) as the social location of the user 18. In addition, when reporting the user login, the reporting function 30 may also report a time at which the user login event occurred. The social location collector 24 may then store the time at which the login event occurred as a timestamp for the social location stored in step 104. Alternatively, the social location collector 24 may store a time at which the report of the user login is received from the reporting function 30 of the web-based social location 14 as the timestamp for the social location stored in step 104. Preferably, both the social location of the user 18 and the timestamp are stored in the user record of the user 18 maintained in the user record repository 26.
  • In this embodiment, in addition to detecting and reporting the login event, the reporting function 30 also detects a user activity performed by the user 18 while at the web-based social location 14 (step 106). The types of user activities that may be detected depends on the web-based social location 14. Different types of user activities may be performed at different types of web-based social locations 14. For example, if the web-based social location 14 is Facebook®, the detected user activity may be, for example, “playing Farmville.”Other types of user activities may be, for example, “chatting,” “posting a message,” “viewing a photo album,” “sharing a photo album,” “watching a video/movie/TV program,” “listening to music/artist/song,” or the like. Upon detecting the user activity, the reporting function 30 reports the user activity to the social browsing system 12 (step 108), and the social location collector 24 stores the user activity and, optionally, a timestamp identifying the time at which the user 18 was performing the user activity in the user record of the user 18 (step 110). Note that steps 102 and 108 may alternatively be combined such that both the social location and the user activity of the user 18 are reported at the same time. From here, the process continues such that the reporting function 30 continues to detect and report user activities of the user 18. In addition, the reporting function 30 reports logins and user activities to the social browsing system 12 for other users 18 in a similar manner.
  • Note that while the reporting in FIG. 2 is event-based (i.e., reporting is triggered in response to a corresponding login/user activity event), the operation of the reporting function 30 is not limited thereto. In an alternative embodiment, the reporting function 30 may collect detected user logins and user activity events over time for a number of the users 18 and report the detected user logins and user activity events to the social browsing system 12 in batches.
  • FIG. 3 illustrates the operation of the social browsing system 12 to collect social locations of the users 18 from the user devices 16 according to one embodiment of the present disclosure. As illustrated, the reporting function 32 of the user device 16 of one of the users 18 detects a social location of the user 18 (step 200). The manner in which the reporting function 32 detects the social location of the user 18 varies depending on the particular implementation of the user device 16. For example, if the user device 16 is a personal computer or other device having web-browsing capabilities, the reporting function 32 may be implemented within a web-browser or as a plug-in to the web-browser of the user device 16 and may detect the social location of the user 18 by monitoring websites visited by the user 18. When the user 18 navigates to a new website, which may be any website or one of a number of predefined websites identified by the user 18 or the social browsing system 12 as being social locations, the reporting function 32 identifies the website as the social location of the user 18. As another example, if the user device 16 is a personal computer or other device having web-browsing capabilities, the reporting function 32 may be implemented within a web-browser or as a plug-in to the web-browser of the user device 16 and may detect the social location of the user 18 by monitoring websites that user 18 has logged into. When the user 18 logs into a new website (e.g., logs into Facebook® or Netflix® online), which may be any website that the user 18 is registered with or one of a number of predefined websites that the user 18 is registered with and that have been identified by the user 18 or the social browsing system 12 as being social locations, the reporting function 32 identifies the website as the social location of the user 18.
  • As another example, if the user device 16 is a personal computer or similar device capable of running a computer-based gaming application (e.g., World of Warcraft® client software), the reporting function 32 may be implemented within the gaming software stored and executed by the user device 16 and may detect when the user 18 starts the gaming application. In response, the gaming application is identified as the social location of the user 18. As yet another example, if the user device 16 is a personal computer, smart phone, or similar device capable of running applications, the reporting function 32 may be implemented within an application or as a plug-in to the application stored and executed by the user device 16, where the application is a social networking application or an application having a social networking feature. The reporting function 32 may detect when the user 18 starts the social networking application or the application having a social networking feature and, in response, identify the application as the social location of the user 18.
  • As another example, if the user device 16 is a gaming console, the reporting function 32 may be implemented within the gaming console and may detect when the user 18 turns on the gaming console and starts playing one of a number of games that are predefined as being social locations. The reporting function 32 may then identify that game as the social location of the user 18. As another example, if the user device 16 is a gaming console, the reporting function 32 may be implemented within a game that is playable by the gaming console, and the reporting function 32 may detect when the game is executed by the gaming console (e.g., loaded into and started by the user 18). That game is then identified as the social location of the user 18.
  • As yet another example, the user device 16 may be a set-top box enabling playback of media content from a media source such as a television service provider, Netflix®, Hulu™, CBS.com, or the like. The reporting function 32 may be implemented within the set-top box. The reporting function 32 may then detect the playback of media content by the user device 16 and identify the media source as the social location of the user 18. Further, if the media source is a television service provider, the social location of the user 18 may be the particular television station (e.g., CBS, NBC, ABC, Fox, TNT, ESPN, etc.).
  • Upon detecting the social location of the user 18, the reporting function 32 reports the social location of the user 18 and, in some embodiments, a time at which the user 18 was detected as being at the social location to the social browsing system 12 (step 202). In response, the social location collector 24 of the social browsing system 12 stores the social location of the user 18 and, in some embodiments, a timestamp for the social location (step 204). If the time at which the social location was detected is provided in step 202, then that time is used as the timestamp for the social location. Otherwise, a time at which the social location is received from the reporting function 32 of the user device 16 may be used as the timestamp for the social location.
  • In this embodiment, in addition to detecting and reporting the social location of the user 18, the reporting function 32 also detects user activity performed by the user 18 while at the social location (step 206). The types of user activities that may be detected depends on the social location. Different types of user activities may be performed for different social locations. For example, the user activity may be “chatting,” “posting a message,” “viewing a photo album,” “sharing a photo album,” “watching a video/movie/TV program,” “listening to music/artist/song,” “playing game X,” “playing a game,” or the like. Upon detecting the user activity, the reporting function 32 reports the user activity to the social browsing system 12 (step 208), and the social location collector 24 stores the user activity and, optionally, a timestamp identifying the time at which the user 18 was performing the user activity in the user record of the user 18 (step 210). Note that steps 202 and 208 may alternatively be combined such that both the social location and the user activity of the user 18 are reported at the same time. From here, the process continues such that the reporting function 32 continues to detect and report the social location and user activities taken by the user 18.
  • Note that while the reporting in FIG. 3 is event-based (i.e., reporting is triggered in response to detecting social location and detecting a user activity event), the operation of the reporting function 32 is not limited thereto. In an alternative embodiment, the reporting function 32 may collect detected social locations and user activity events over time for the user 18 and report the detected social locations and user activity events to the social browsing system 12 in batches.
  • FIG. 4 illustrates the operation of the social browsing system 12 to generate social crowd data for a number of social locations according to one embodiment of the present disclosure. In this embodiment, the social browsing system 12 first receives a social crowd request from one of the user devices 16 (step 300). In the preferred embodiment, the social crowd request is sent by the visualization function 36 of the user device 16 automatically or upon request by the user 18 of the user device 16. More specifically, in one embodiment, the visualization function 36 sends the social crowd request to the social browsing system 12 in response to activation of a Graphical User Interface (GUI) provided by the visualization function 36 by the user 18 of the user device 16.
  • In response to the social crowd request, the request processor 28 generates social crowd data for social crowds at a number of social locations identified for the social crowd request (step 302). In one embodiment, the social crowd request identifies one or more social locations for which social crowd data is desired. In another embodiment, the user 18 of the user device 16 has preconfigured which social locations that the user 18 is interested in and those social locations are stored in the user record of the user 18 in the user record repository 26. In another embodiment, the user 18 of the user device 16 has selected one or more types of social locations (e.g., social networking services/applications, games, media sharing, or the like) in which the user 18 is interested, and the social locations identified for the social crowd request are social locations of the selected type(s). In yet another embodiment, the social locations identified for the social crowd request may be system-defined and may be the same for all of the users 18 or may vary for different groups of the users 18 (e.g., different demographic groups).
  • While discussed below in detail, in general, the social crowd data for each social location identified for the social crowd request is generated by first identifying a social crowd for the social location. The social crowd for the social location is a group of the users 18 that are currently at the social location, a group of the users 18 that were historically at the social location (i.e., at the social location within one or more defined historical time periods), or a group of the users 18 including those users 18 that are currently at the social location and those users 18 that were historically at the social location, depending on the particular implementation. Then, an aggregate profile for the social crowd at the social location is generated. In the preferred embodiment, based on the aggregate profile of the social crowd, an affinity between the user 18 of the user device 16 (i.e., the requesting user) and the social crowd at the social location is determined. The social crowd data then preferably includes the affinities between the user 18 of the user device 16 and the social crowds at the social locations identified for the social crowd request. In addition, the social crowd data preferably includes a number of users in each of the social crowds.
  • However, it should be noted that the social crowd data is not limited to including the affinities between the user 18 of the user device 16 and the social crowds and, optionally, the number of users in each of the social crowds. For example, in another embodiment, the social crowd data may additionally or alternatively include the aggregate profiles for the social crowds. The aggregate profile for a social crowd includes an aggregate, or merged, list of interests from the user profiles of the users 18 in the social crowd. In addition, the aggregate profile may include, for each interest in the aggregate profile, a number of user matches, or occurrences, of the interest among the users 18 in the social crowd or a ratio of the number of user matches for the interest to a total number of users in the social crowd.
  • In another embodiment, the social crowd data may alternatively include predicted, or future, social crowd data for the one or more social locations identified for the social crowd request. More specifically, in order to provide the predicted social crowd data for one of the social locations, the request processor 28 obtains social crowd data for the social location (e.g., an affinity between the requesting user 18 and the social crowd and the number of users in the social crowd) for a number of times or time periods in the past. For example, the request processor 28 may obtain social crowd data for the social location for each day of the last month. Then, using known statistical algorithms, the request processor 28 may determine a trend for the social crowd data (e.g., a trend for the affinity between the requesting user 18 and the social crowd at the social location and a trend in the number of users in the social crowd at the social location) over the last month. This trend is used to provide the predicted social crowd data (e.g., predicted affinity between the requesting user 18 and the social crowd at the social location and the number of users in the social crowd at the social location) for the social location at a desired time in the future.
  • Next, the request processor 28 returns the social crowd data for the social crowds identified for the social locations to the user device 16 (step 304). In response, the visualization function 36 of the user device 16 visualizes the social crowd data and presents resulting visualized social crowd data to the user 18 at the user device 16 (step 306). More specifically, in the preferred embodiment, the visualization function 36 provides a GUI that includes a representation (e.g., an icon, screenshot, or the like) for each of at least a subset of the social locations identified for the social crowd request. Within the GUI, for each representation, a visual characteristic (e.g., color, size, or the like) of the representations is controlled to be indicative of the affinity between the user 18 of the user device 16 and the social crowd at the corresponding social location (i.e., the social location represented by the representation in the GUI). In addition, for each representation in the GUI, a second visual characteristic (e.g., color, size, or the like) may be controlled to be indicative of the number of users in the social crowd at the corresponding social location. In one embodiment, the GUI initially includes representations for a predefined number of the social locations identified for the social crowd request having social crowds with the highest affinities to the user 18 of the user device 16. The user 18 may then be enabled to navigate the GUI to view representations for more social locations, if any. Using the GUI presented by the visualization function 36, the user 18 is enabled to quickly and easily see social locations at which other users 18 that are like him are currently located and/or have historically been located.
  • Further, the GUI provided by the visualization function 36 may enable the user 18 to go to a desired social location by, for example, selecting the representation of the desired social location in the GUI. The GUI may also enable the user 18 to view additional information regarding the social crowds at the social locations. For example, upon selecting a representation of a social location in the GUI, the visualization function 36 may present, via the GUI, information regarding the social crowd at the social location such as, for example, an affinity score representing the affinity between the user 18 and the social crowd, a number that is the number of users 18 in the social crowd, the aggregate profile for the social crowd, information identifying the users 18 in the social crowd (e.g., birth names, usernames, pictures, or the like), a number that is a number of the users 18 in the social crowd that are in a social network of the user 18, information identifying the users 18 in the social crowd that are in a social network of the user 18, or the like.
  • FIG. 5 is a flow chart illustrating the operation of the request processor 28 of the social browsing system 12 in more detail according to one embodiment of the present disclosure. First, the request processor 28 of the social browsing system 12 receives a social crowd request from the user device 16 of a requesting user 18 (step 400). The request processor 28 then gets the next social location from one or more social locations identified for the social crowd request (step 402). Next, the request processor 28 identifies a social crowd for the social location (step 404). In one embodiment, the social crowd for the social location is a group of the users 18 currently at the social location. In order to identify the users 18 currently at the social location, the request processor 28 queries the user record repository 26 for the users 18 that are currently at the social location. The users 18 currently at the social location may be those users 18 whose last reported social locations are the social location. Alternatively, the users 18 currently at the social location may be those users 18 whose last reported social locations are the social location and the corresponding timestamps indicate that those users 18 were at the social location during a predefined time period prior to the current time (e.g., within the last 10 minutes). Here, the predefined time period prior to the current time is relatively short in order to reflect that the users 18 are “currently” at the social location.
  • Note that, in some embodiments, the users 18 may be currently at more than one social location (e.g., using Facebook® and Twitter® while watching a movie). In this case, the users 18 currently at the social location may be those users 18 that have been reported to be at the social location during a predefined time period prior to the current time (e.g., the last 10 minutes), as indicated by the social locations and corresponding timestamps stored in the user record of the user 18. Here again, the predefined time period prior to the current time is relatively short in order to reflect that the users 18 are “currently” at the social location.
  • When identifying the users 18 that are currently at the social location, the request processor 28 may consider the user activities reported for the users 18 in addition to the social locations reported for the users 18. More specifically, in one embodiment, the users 18 currently at the social location may be those users 18 whose last reported social locations are the social location (or who were reported to be at the social location within a predefined time period prior to the current time such as, for example, the last two hours) and the reported user activities for those users 18 indicate that the users 18 have performed a user activity at the social location within a predefined relatively short time period prior to the current time (e.g., within the last 10 minutes). As yet another alternative, the users 18 currently at the social location may be those users 18 whose last reported social locations are the social location (or who were reported to be at the social location within a predefined time period prior to the current time such as, for example, the last two hours) and: (1) the corresponding timestamps indicate that those users 18 were at the social location within a predefined relatively short time period prior to the current time (e.g., within the last 10 minutes) and/or (2) the reported user activities for those users 18 indicate that the users 18 have performed a user activity at the social location within a predefined period of time relative to the current time (e.g., within the last 10 minutes).
  • In another embodiment, the social crowd for the social location is a group of the users 18 who were historically, or previously, at the social location during one or more defined historical periods of time (e.g., last Friday, all Fridays over the past six months, the last week, Apr. 1, 2010, or the like). The historical periods of time are preferably defined by the requesting user 18, but may alternatively be system-defined time periods. The request processor 28 queries the user record repository 26 to identify the users 18 that were at the social location during the one or more historical periods of time. The users 18 at the social location during the one or more historical periods of time may be those users 18 having social locations and corresponding timestamps that indicate that the users 18 were at the social location during the one or more historical periods of time. Alternatively, the users 18 at the social location during the one or more historical periods of time may be those users 18 having social locations and corresponding timestamps and reported user activities and corresponding timestamps that indicate that the users 18 were at the social location during the one or more historical periods of time. In yet another embodiment, the social crowd for the social location includes both the users 18 that are currently at the social location and the users 18 that were at the social location during one or more defined historical periods of time.
  • In this embodiment, the social crowd identified for the social location is filtered based on one or more filtering criteria (step 406). Note that the filtering step 406 is optional. Also note that while steps 404 and 406 are illustrated separately for clarity, it should be appreciated that steps 404 and 406 may be implemented as a single operation (e.g., a single query). The one or more filtering criteria preferably include one or more user-defined filtering criteria defined by the requesting user 18. These user-defined filtering criteria may be included in the social crowd request or stored in the user record of the requesting user 18. The filtering criteria may include, for example, a status criterion, a maximum degree of separation in a social network of the requesting user 18, a user activity criterion, a physical location criterion, or a combination thereof. With respect to the status criterion, the social crowd may be filtered to remove the users 18 that are not currently online or connected to the network 20, to remove the users 18 that have been online less than a defined threshold amount (e.g., less than one hour a day for the last week), or the like.
  • With respect to the maximum degree of separation, the social crowd may be filtered to remove the users in the social crowd that are not within a defined maximum degree of separation, or social network distance, from the requesting user 18 in a social network (e.g., the Facebook® social network, the MySpace® social network, or the like). More specifically, in one embodiment, the user records of the users 18 include the Facebook® usernames of the users 18. The request processor 28 may then query Facebook® via, for example, an Application Programming Interface (API) to determine the degree of separation between the requesting user 18 and each of the users 18 in the social crowd. The social crowd may then be filtered to remove the users 18 that are not within the defined maximum degree of separation from the requesting user 18. The defined maximum degree of separation is preferably defined by the user 18. With respect to the user activity criterion, the social crowd may be filtered to remove the users 18 that are currently performing one or more defined user activities. Alternatively, the social crowd may be filtered to remove the users 18 that are not currently performing one or more defined user activities.
  • With respect to the physical location criterion, the social crowd may be filtered to remove users that are not physically located within a defined geographic area. The defined geographic area may be a static geographic area such as, for example, a particular city, a particular zip code, a particular state, or the like. Alternatively, the defined geographic area may be a relative geographic area such as, for example, within ten miles from the requesting user 18. Note that the physical locations of the users 18 may be obtained in any suitable manner. For example, in one embodiment, the user devices 16 of the users 18 determine and report the physical locations of the user devices 16 to the social browsing system 12 as the physical locations of the users 18. The user devices 16 may obtain the physical locations of user devices 16 using any suitable technology such as, for example, Global Positioning System (GPS) receivers, manual input of the physical locations by the users 18, lookup of physical location from a remote source based on Wi-Fi® access point, or the like.
  • After the optional filtering step, the request processor 28 obtains an aggregate profile for the social crowd (step 408). More specifically, in this embodiment, the user records of the users 18 include the user profiles of the users 18, and the request processor 28 obtains the user profiles of the users 18 in the social crowd from their user records and provides the user profiles of the users 18 in the social crowd to the aggregate profile server 22 for aggregation. In response, the request processor 28 receives the aggregate profile of the social crowd from the aggregate profile server 22. The aggregate profile of the social crowd includes an aggregate list of interests from the user profiles of the users 18 in the social crowd. In addition, the aggregate profile of the social crowd may include a number of user matches, or occurrences, of each of the interests in the aggregate list of interests across all of the user profiles of the users 18 in the social crowd or a ratio of the number of user matches for each of the interests to a total number of users 18 in the social crowd.
  • Before proceeding, it should be noted that in an alternative embodiment, the functionality of the aggregate profile server 22 is integrated into the social browsing system 12 such that the aggregate profile of the social crowd is generated by the social browsing system 12. In another alternative embodiment, rather than being stored in the user records of the users 18 in the user record repository 26 of the social browsing system 12, the user profiles of the users 18 may be stored by the aggregate profile server 22. In this case, the request processor 28 provides information identifying the users 18 in the social crowd to the aggregate profile server 22. In response, the aggregate profile server 22 obtains the user profiles of the users 18 in the social crowd and aggregates the user profiles of those users 18 to provide the aggregate profile of the social crowd. In yet another embodiment, the user profiles of the users 18 may be stored by a third-party application or service (e.g., Facebook®). In this case, the request processor 28 may obtain the user profiles of the users 18 in the social crowd from the third-party application or service and provide the user profiles to the aggregate profile server 22 for aggregation. Alternatively, the request processor 28 may provide information identifying the users 18 in the social crowd to the aggregate profile server 22, where the aggregate profile server 22 then obtains the user profiles of those users from the third-party service or application and aggregates the user profiles to provide the aggregate profile of the social crowd.
  • Next, the request processor 28 determines an affinity between the requesting user 18 and the social crowd based on a comparison of the aggregate profile for the social crowd and the user profile of the requesting user 18 (step 410). In one embodiment, the affinity between the requesting user 18 and the social crowd is a function of the number of user interests in the user profile of the requesting user 18 that match interests in the aggregate profile of the social crowd. For example, the affinity between the requesting user 18 and the social crowd may be the number of interests in the user profile of the requesting user 18 that match user interests in the aggregate profile of the social crowd. As another example, the affinity between the requesting user 18 and the social crowd may be a ratio of the number of interests in the user profile of the requesting user 18 that match user interests included in the aggregate profile of the social crowd over a total number of interests in the user profile of the requesting user 18. As yet another example, the affinity between the requesting user 18 and the social crowd may be a percentage of the user interests in the user profile of the requesting user 18 that match interests in the aggregate profile of the social crowd.
  • In another embodiment, the affinity between the requesting user 18 and the social crowd is a function of the number of interests in the user profile of the requesting user 18 that match user interests in the aggregate profile for the social crowd and the number of user matches for the interests in the aggregate profile or the ratio of the number of user matches for the interests in the aggregate profile over the total number of users 18 in the social crowd. For example, the affinity between the requesting user 18 and the social crowd may be the number of interests in the user profile of the requesting user 18 that match one or more interests in the aggregate profile for the social crowd that have the highest M user matches or ratios of user matches to total number of users. Here, M may be an integer greater than or equal to 1 and may be system-defined or configurable by the requesting user 18.
  • Note that the techniques for determining the affinity between the requesting user 18 and the social crowd based on the aggregate profile of the social crowd and the user profile of the requesting user 18 described above are exemplary. Other techniques will be apparent to one of ordinary skill in the art upon reading this disclosure. Further, it should also be noted that, in one embodiment, an interest in the user profile of the requesting user 18 “matches” an interest in the aggregate profile of the social crowd if the two interests match exactly. In another embodiment, an interest in the user profile of the requesting user 18 “matches” an interest in the aggregate profile of the social crowd if the two interests match to a predefined threshold degree. The predefined threshold degree may be system-defined or defined by the requesting user 18. For example, an ontology or similar data structure, or service providing such an ontology or data structure such as, for example, Wikipedia®, may be utilized to determine a degree of similarity between two interests. In general, the ontology or data structure defines direct and indirect relationships between terms in much the same manner as a social network defines direct and indirect relationships between users. Thus, an ontology or similar data structure may define that “NC State University” is directly related to “Philip Rivers,” and that “Philip Rivers” is directly related to “San Diego Chargers.” As such, “NC State University” may be said to exactly match “North Carolina State University” (0 degrees of separation), to be directly related to “Philip Rivers” (1 degree of separation), and to be indirectly related to “San Diego Chargers” (2 degrees of separation). The predefined threshold may be set such that two interests “match” if they are within a defined degree of separation from one another in the ontology or similar data structure.
  • Once the affinity between the requesting user 18 and the social crowd has been determined, the request processor 28 determines whether the last social location of the one or more social locations identified for the social crowd request has been processed (step 412). If not, the process returns to step 402 and is repeated for the next social location. Once all of the social locations identified for the social crowd request have been processed, the request processor 28 returns social crowd data to the user device 16 of the requesting user 18, where the social crowd data includes the affinities between the requesting user 18 and the social crowds identified for the social locations and, optionally, the number of users in each of the social crowds (step 414).
  • Before proceeding, an alternative embodiment should be discussed. In the embodiment described above, an aggregate profile is first obtained for a social crowd, and then an affinity between the requesting user 18 and the social crowd is determined based on a comparison of the aggregate profile of the social crowd and the user profile of the requesting user 18. However, the present disclosure is not limited thereto. In another embodiment, the affinity between the requesting user 18 and the social crowd may be determined by directly comparing the user profile of the requesting user 18 and the user profiles of the users 18 in the social crowd. Based on the comparison, the affinity between the requesting user 18 and the social crowd may be represented as, for example, a total number of user matches for all of the interests in the user profile of the requesting user 18 across all of the user profiles of the users 18 in the social crowd. As another example, the affinity between the requesting user 18 and the social crowd may be represented as a percentage or ratio of the users 18 in the social crowd having user profiles that include at least one interest that matches an interest in the user profile of the requesting user 18.
  • FIG. 6 illustrates an exemplary GUI 38 provided by the visualization function 36 of the social browsing client 34 of one of the user devices 16 according to one embodiment of the present disclosure. As illustrated, the GUI 38 includes a number of representations 40-1 through 40-7 (also generally referred to herein as representations 40 or representation 40). Each representation 40 represents one of the social locations identified for a social crowd request issued by the visualization function 36. In this example, color (which is represented by shading) of borders 42-1 through 42-7 (also generally referred to herein as borders 42 or border 42) of the representations 40-1 through 40-7 is controlled such that the color (shading) of the borders 42-1 through 42-7 is indicative of the affinity between the user 18 of the user device 16 and the social crowds identified for the social locations represented by the representations 40-1 through 40-7. Thus, in this example, the affinities between the user 18 and the social crowds identified for the social locations represented by the representations 40-1 and 40-4 are low as indicated by the light shading of the borders 42-1 and 42-4, the affinities between the user 18 and the social crowds identified for the social locations represented by the representations 40-2, 40-5, and 40-6 are moderate as indicated by the moderate shading of the borders 42-2, 42-5, and 42-6, and the affinities between the user 18 and the social crowds identified for the social locations represented by the representations 40-3 and 40-7 are high as indicated by the dark shading of the borders 42-3 and 42-7.
  • In addition, in this embodiment, sizes of the representations 40 are controlled to be indicative of the number of users in the social crowds for the represented social locations. Thus, in this example, the social crowds identified for the social locations represented by the representations 40-1 and 40-7 each have a large number of users, the social crowds identified for the social locations represented by the representation 40-6 has a moderate number of users, and the social crowds identified for the social locations represented by the representations 40-2 through 40-5 each have a small number of users.
  • In this embodiment, the GUI 38 also includes a user settings area 44 that enables the user 18 to configure, or define, a number of settings. More specifically, in this example, the user settings area 44 includes a slider bar 46 that enables the user 18 to configure a social distance filtering criteria that defines the maximum degree of separation to be used to filter social crowds, and a slider bar 48 that enables the user 18 to configure the online status filtering criteria to be used to filter social crowds. In addition, the user settings area 44 includes a slider bar 50 that enables the user 18 to configure a threshold degree of similarity to be used when determining the affinity between the user 18 and social crowds, as described above.
  • Lastly, in this embodiment, the user settings area 44 includes radio buttons 52-1 through 52-3 (also generally referred to herein as radio buttons 52 or radio button 52) that enable the user 18 to identify one or more types of social locations in which the user 18 is interested. Note that the radio buttons 52 shown are exemplary. Similar buttons for additional or alternative types of social locations may be included. In this example, the user 18 has selected the radio buttons 52 for “Social Network Services/Apps” and “Gaming Services/Apps.” As such, social crowd data is requested and returned for only social locations that are social networking services or applications or gaming services or applications. While not illustrated, in a similar manner, the user 18 may be enabled to select one or more user activities such that social crowds are filtered to remove users other than those who participate in the one or more selected user activities.
  • Before proceeding, it should be noted that while the discussion herein focuses on presenting representations for the social locations to the requesting user 18, the present disclosure is not limited thereto. For example, in one embodiment, the visualization function 36 of the user device 16 may present a representation for each of a number of social location types such as, for example, social networking services or applications, gaming services or applications, media applications or services (e.g., streaming video services, television services, or the like), media sharing applications or services, news websites, or the like. Visual characteristics of the representations for the social location types may be controlled to be indicative of the combined social crowd data for the corresponding social locations. For example, the representation for a social location type may have a first visual characteristic that is controlled to be indicative of an average affinity between the requesting user 18 and the social crowds identified for social locations of the social location type and a second visual characteristic that is controlled to be indicative of an average number of users in the social crowds identified for the social locations of the social location type.
  • In another embodiment, the visualization function 36 of the user device 16 may present a representation for each of a number of user activities (e.g., playing a game, watching a movie, etc.). Visual characteristics of the representations may be controlled to be indicative of the combined social crowd data for the corresponding social locations. For example, for a particular user activity, the social locations at which user(s) are or have performed the user activity are identified. The crowd data for the identified social locations is then combined to provide the combined social crowd data for the user activity (e.g., average affinity, average number of users, or the like). One or more visual characteristics of the representation of the user activity in the GUI provided by the visualization function 36 may then be controlled to be indicative of the combined social crowd data for the social location. The visualization function 36 may further enable the user 18 to select the representation for one of the user activities in order to cause the visualization function 36 to present representations for the social locations identified for the user activity to the user 18 in a manner similar to that shown in FIG. 6.
  • FIGS. 7 and 8 illustrate alternative embodiments of the system 10 of FIG. 1. Specifically, FIG. 7 illustrates an alternative embodiment of the system 10 wherein the social browsing system 12 is incorporated into an existing system, which in this embodiment is a social networking system 54 hosting a social networking service (e.g., Facebook®). In this embodiment, the social browsing system 12 is preferably implemented in software and the user profiles of the users 18 utilized by the social browsing system 12 are preferably user profiles of the users 18 maintained by the social networking system 54 for the social networking service. Otherwise, the system 10 of FIG. 7 is the same as and operates the same as described above.
  • FIG. 8 illustrates another alternative embodiment of the system 10 of FIG. 1. In this embodiment, the social locations of the users 18 and, in some embodiments, the user activities of the users 18 are reported to a third-party presence service 56. The social browsing system 12 obtains the social locations and, in some embodiments, the user activities of the users 18 from the presence service 56. In one embodiment, the reporting functions 32 of the user devices 16 report the social locations and user activities of the users 18 to the presence service 56 using a standard such as the Session Initiation Protocol for Instant Messaging and Presence Leveraging Extensions (SIMPLE). Specifically, the Rich Presence Information Data Format (RPID), which is an extension of the Presence Information Data Format (PIDF), may be used to send the social locations and user activities of the users 18 to the presence service 56 as presence information. For example, the reporting function 32 may report the social location of the user 18 by providing a user ID of the user 18 recognized by the social browsing system 12, the social location of the user 18, and a timestamp defining a time at which the user 18 was at the social location to the presence service 56. The presence service 56 may then provide this information to the social browsing system 12 automatically or as requested by the social browsing system 12. Otherwise, the system 10 of FIG. 8 is the same as and operates the same as described above.
  • FIG. 9 is a block diagram of the social browsing system 12 of FIG. 1 according to one embodiment of the present disclosure. As illustrated, the social browsing system 12 includes a controller 58 connected to memory 60, one or more secondary storage devices 62, and a communication interface 64 by a bus 66 or similar mechanism. The controller 58 is a microprocessor, digital Application Specific Integrated Circuit (ASIC), Field Programmable Gate Array (FPGA), or the like. In this embodiment, the controller 58 is a microprocessor, and the social location collector 24 and the request processor 28 (FIG. 1) are implemented in software and stored in the memory 60 for execution by the controller 58. The secondary storage devices 62 are digital data storage devices such as, for example, one or more hard disk drives. The user record repository 26 (FIG. 1) may be implemented in the one or more secondary storage devices 62. The communication interface 64 is a wired or wireless communication interface that communicatively couples the social browsing system 12 to the network 20 (FIG. 1). For example, the communication interface 64 may be an Ethernet interface, local wireless interface such as a wireless interface operating according to one of the suite of IEEE 802.11 standards, or the like.
  • FIG. 10 is a block diagram of the social networking system 54 hosting the social browsing system 12 of FIG. 7 according to one embodiment of the present disclosure. As illustrated, the social networking system 54 includes a controller 68 connected to memory 70, one or more secondary storage devices 72, and a communication interface 74 by a bus 76 or similar mechanism. The controller 68 is a microprocessor, digital ASIC, FPGA, or the like. In this embodiment, the controller 68 is a microprocessor, and the social browsing system 12 is at least partially implemented in software stored in the memory 70 for execution by the controller 68. The secondary storage devices 72 are digital data storage devices such as, for example, one or more hard disk drives. The communication interface 74 is a wired or wireless communication interface that communicatively couples the social networking system 54 to the network 20 (FIG. 7). For example, the communication interface 74 may be an Ethernet interface, local wireless interface such as a wireless interface operating according to one of the suite of IEEE 802.11 standards, or the like.
  • FIG. 11 is a block diagram of the one of the user devices 16 according to one embodiment of the present disclosure. As illustrated, the user device 16 includes a controller 78 connected to memory 80, one or more secondary storage devices 82, a communication interface 84, and one or more user interface components 86 by a bus 88 or similar mechanism. The controller 78 is a microprocessor, digital ASIC, FPGA, or the like. In this embodiment, the controller 78 is a microprocessor, and the reporting function 32 and the social browsing client 34 (FIGS. 1, 7, and 8) are implemented in software and stored in the memory 80 for execution by the controller 78. The one or more secondary storage devices 82 are digital storage devices such as, for example, one or more hard disk drives. The communication interface 84 is a wired or wireless communication interface that communicatively couples the user device 16 to the network 20 (FIGS. 1, 7, and 8). For example, the communication interface 84 may be an Ethernet interface, local wireless interface such as a wireless interface operating according to one of the suite of IEEE 802.11 standards, a mobile communications interface such as a cellular telecommunications interface, or the like. The one or more user interface components 86 include, for example, a touchscreen, a display, one or more user input components (e.g., a keypad), a speaker, or the like, or any combination thereof.
  • The following use cases illustrate some but not necessarily all of the concepts discussed above. Further, the following use cases are exemplary and are not intended to limit the scope of the present disclosure or the claims that follow.
  • Bob is stuck at home with nothing to do, but he is eager to interact with someone, either friends or people with interests similar to his own. Bob launches the visualization function 36 of the social browsing client 34 on his user device 16. The visualization function 36 obtains social crowd data for a number of social locations from the social browsing system 12 according to parameters, or settings, that Bob has defined (e.g., filtering criteria). Based on the social crowd data, the visualization function 36 provides graphical representations, or indicators, for each of a number of social locations where visual characteristic(s) of the graphical representations are controlled to be indicative of the social crowd data for the corresponding social locations. Bob can refine this view by modifying his settings such as, for example, selecting the type(s) of social locations in which he is interested. Alternatively, Bob may be enabled to search for social locations of a desired type such as, for example, Sports websites. The visualization function 36 will then modify the graphical representations presented to Bob to include only graphical representations for the desired type(s) of social locations. Note that the visualization function 36 requests additional social crowd data from the social browsing system 12 as needed. Using the GUI output by the visualization function 36, Bob is enabled to quickly see what social locations other users like himself are currently at, have historically been at, or are predicted to be at in the future, depending on the particular implementation.
  • Bob wants to interact with someone. Therefore, he sets the Online Status filtering criterion to “currently online.” Bob will interact with almost anyone, so he sets his Maximum Degree of Separation filtering criterion fairly high. In response, the visualization function 36 presents graphical representations for a number of social locations that visualize the number of users in the social crowds by the sizes of the corresponding graphical representations and the affinities between Bob and the social crowds at the social locations by the color of the corresponding graphical representations. Bob can mouse over the graphical representations to view more detailed information regarding the type of activity, more user details, etc. By clicking on a graphical representation, Bob can go to the corresponding social locations (e.g., go to the website, launch the application, or the like).
  • As another use case, Bob is looking for social locations that he may want to join. More specifically, Bob is looking to become more engaged in the online social networking world. Bob sets the parameters in the system as follows: maximum degree of separation is set to a maximum value (i.e., all users are included—users in social crowds are not required to be directly or indirectly related to Bob in a social network), online status is set to allow any users that have been online (e.g., logged in) within the past week, match strength is set to a maximum value, and social networking sites/applications are the only desired social location type.
  • In response, the visualization function 36 of Bob's user device 16 obtains social crowd data for the appropriate social locations, visualizes the social crowd data, and presents the resulting visualized social crowd data to Bob.
  • Again, in this example, the social locations may be represented as corresponding graphical representations having sizes and colors that are controlled to be indicative of the number of users in the social crowds identified for the corresponding social locations and the affinities between Bob and the social crowds identified for the corresponding social locations. Bob quickly notices that his best bet is to try out Facebook® and maybe MySpace® later. Bob clicks on the graphical representation for Facebook®, joins, and quickly links up with several people with similar interests.
  • Those skilled in the art will recognize improvements and modifications to the preferred embodiments of the present disclosure. All such improvements and modifications are considered within the scope of the concepts disclosed herein and the claims that follow.

Claims (28)

What is claimed is:
1. A computer-implemented method comprising:
receiving a social crowd request from a user device of a requesting user;
identifying a social crowd for each social location of one or more social locations identified for the social crowd request;
for each social location of the one or more social locations, obtaining social crowd data for the social crowd for the social location; and
returning the social crowd data for the one or more social locations to the user device of the requesting user.
2. The method of claim 1 wherein identifying the social crowd for each social location comprises, for each social location of the one or more social locations, identifying a plurality of users currently at the social location as the social crowd for the social location.
3. The method of claim 1 wherein identifying the social crowd for each social location comprises, for each social location of the one or more social locations, identifying a plurality of users previously at the social location during one or more defined historical periods of time as the social crowd for the social location.
4. The method of claim 1 wherein identifying the social crowd for each social location comprises, for each social location of the one or more social locations, identifying a plurality of users currently at the social location and a plurality of users previously at the social location during one or more defined historical periods of time as the social crowd for the social location.
5. The method of claim 1 wherein each social location of the one or more social locations is a service or application in which users participate.
6. The method of claim 5 wherein the service or application is a social networking service or application.
7. The method of claim 5 wherein the service or application is a service or application having a social networking feature.
8. The method of claim 1 wherein, for each social location of the one or more social locations, the social crowd data for the social crowd for the social location comprises an affinity between the requesting user and the social crowd.
9. The method of claim 1 wherein, for each social location of the one or more social locations, the social crowd data for the social crowd for the social location comprises a number of users in the social crowd.
10. The method of claim 1 wherein, for each social location of the one or more social locations, the social crowd data for the social crowd for the social location comprises an affinity between the requesting user and the social crowd and a number of users in the social crowd.
11. The method of claim 1 wherein, for each social location of the one or more social locations, obtaining the social crowd data for the social crowd for the social location comprises:
obtaining an aggregate profile for the social crowd; and
determining an affinity between the requesting user and the social crowd based on a comparison of a user profile of the requesting user and the aggregate profile of the social crowd.
12. The method of claim 1 wherein, for each social location of the one or more social locations, obtaining the social crowd data for the social crowd for the social location comprises determining an affinity between the requesting user and the social crowd based on a comparison of a user profile of the requesting user and user profiles of a plurality of users in the social crowd.
13. The method of claim 1 further comprising:
collecting social locations of a plurality of users over time;
wherein, for each social location of the one or more social locations identified for the social crowd request, the social crowd identified for the social location comprises a subset of the plurality of users identified for the social location based on the social locations collected for the subset of the plurality of users.
14. The method of claim 1 further comprising for each social location of the one or more social locations identified for the social crowd request, filtering the social crowd identified for the social location based on one or more filtering criteria prior to obtaining the social crowd data for the social crowd for the social location.
15. The method of claim 14 wherein the one or more filtering criteria comprises a criterion based on online status.
16. The method of claim 14 wherein the one or more filtering criteria comprises a maximum degree of separation from the requesting user in a social network.
17. The method of claim 14 wherein filtering the social crowd comprises removing users from the social crowd that are physically located outside of a desired geographic area defined by at least one of the one or more filtering criteria.
18. A server comprising:
a communication interface communicatively coupling the server to a network; and
a controller associated with the communication interface and adapted to:
receive a social crowd request from a user device of a requesting user;
identify a social crowd for each social location of one or more social locations identified for the social crowd request;
for each social location of the one or more social locations, obtain social crowd data for the social crowd for the social location; and
return the social crowd data for the one or more social locations to the user device of the requesting user.
19. A computer readable medium storing software for instructing a controller of a computing device to:
receive a social crowd request from a user device of a requesting user;
identify a social crowd for each social location of one or more social locations identified for the social crowd request;
for each social location of the one or more social locations, obtain social crowd data for the social crowd for the social location; and
return the social crowd data for the one or more social locations to the user device of the requesting user.
20. A computer-implemented method comprising:
obtaining social crowd data for one or more social crowds identified for one or more social locations, each social crowd of the one or more social crowds identified for a social location of the one or more social locations; and
for each social location of at least a subset of the one or more social locations, presenting a representation representative of the social location to a user via a Graphical User Interface (GUI) such that one or more visual characteristics of the representation are controlled based on the social crowd data for the social crowd identified for the social location.
21. The method of claim 20 wherein, for each social location of the one or more social locations, the social crowd data for the social crowd identified for the social location comprises an affinity between the user and the social crowd identified for the social location.
22. The method of claim 21 wherein, for each social location of the at least a subset of the one or more social locations, presenting the representation representative of the social location comprises presenting the representation representative of the social location to the user via the GUI such that a visual characteristic of the representation is controlled to be indicative of the affinity between the user and the social crowd identified for the social location.
23. The method of claim 20 wherein, for each social location of the one or more social locations, the social crowd data for the social crowd identified for the social location comprises a number of users in the social crowd identified for the social location.
24. The method of claim 23 wherein, for each social location of the at least a subset of the one or more social locations, presenting the representation representative of the social location comprises presenting the representation representative of the social location to the user via the GUI such that a visual characteristic of the representation is controlled to be indicative of the number of users in the social crowd identified for the social location.
25. The method of claim 20 wherein, for each social location of the one or more social locations, the social crowd data for the social crowd identified for the social location comprises an affinity between the user and the social crowd identified for the social location and a number of users in the social crowd identified for the social location.
26. The method of claim 25 wherein, for each social location of the at least a subset of the one or more social locations, presenting the representation representative of the social location comprises presenting the representation representative of the social location to the user via the GUI such that a first visual characteristic of the representation is controlled to be indicative of the affinity between the user and the social crowd identified for the social location and a second visual characteristic of the representation is controlled to be indicative of the number of users in the social crowd identified for the social location.
27. A user device comprising:
a communication interface communicatively coupling the user device to a remote system via a network; and
a controller associated with the communication interface and adapted to:
obtain social crowd data for one or more social crowds identified for one or more social locations from the remote system, each social crowd of the one or more social crowds identified for a social location of the one or more social locations; and
for each social location of at least a subset of the one or more social locations, present a representation representative of the social location to a user via a Graphical User Interface (GUI) such that one or more visual characteristics of the representation are controlled based on the social crowd data for the social crowd identified for the social location.
28. A computer readable medium storing software for instructing a controller of a computing device to:
obtain social crowd data for one or more social crowds identified for one or more social locations, each social crowd of the one or more social crowds identified for a social location of the one or more social locations; and
for each social location of at least a subset of the one or more social locations, present a representation representative of the social location to a user via a Graphical User Interface (GUI) such that one or more visual characteristics of the representation are controlled based on the social crowd data for the social crowd identified for the social location.
US12/769,802 2009-04-29 2010-04-29 System and method for social browsing using aggregated profiles Abandoned US20120047448A1 (en)

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US12/759,749 Abandoned US20120046995A1 (en) 2009-04-29 2010-04-14 Anonymous crowd comparison
US12/764,143 Abandoned US20120046068A1 (en) 2009-04-29 2010-04-21 Automatically performing user actions based on detected context-to-user-action correlations
US12/764,150 Expired - Fee Related US8554770B2 (en) 2009-04-29 2010-04-21 Profile construction using location-based aggregate profile information
US12/764,148 Abandoned US20120047565A1 (en) 2009-04-29 2010-04-21 Proximity-based social graph creation
US12/768,973 Abandoned US20120046017A1 (en) 2009-04-29 2010-04-28 System and method for prevention of indirect user tracking through aggregate profile data
US12/769,031 Abandoned US20120047152A1 (en) 2009-04-29 2010-04-28 System and method for profile tailoring in an aggregate profiling system
US12/769,802 Abandoned US20120047448A1 (en) 2009-04-29 2010-04-29 System and method for social browsing using aggregated profiles
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US12/764,150 Expired - Fee Related US8554770B2 (en) 2009-04-29 2010-04-21 Profile construction using location-based aggregate profile information
US12/764,148 Abandoned US20120047565A1 (en) 2009-04-29 2010-04-21 Proximity-based social graph creation
US12/768,973 Abandoned US20120046017A1 (en) 2009-04-29 2010-04-28 System and method for prevention of indirect user tracking through aggregate profile data
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US20140095516A1 (en) 2014-04-03

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