WO2014172827A1

WO2014172827A1 - A method and apparatus for acquaintance management and privacy protection

Info

Publication number: WO2014172827A1
Application number: PCT/CN2013/074504
Authority: WO
Inventors: Alvin CHIN; Jilei Tian
Original assignee: Nokia Corporation; Nokia (China) Investment Co. Ltd.
Priority date: 2013-04-22
Filing date: 2013-04-22
Publication date: 2014-10-30

Abstract

A method for acquaintance management and privacy protection may comprise: obtaining user data for sharing on a social network from a first user; performing an analysis on the user data to identify one or more entities associated with the user data in the social network, wherein the one or more entities comprise at least one user, at least one group, or a combination thereof; and suggesting to the first user a list of candidate recipients with which the user data is to be shared, wherein the list of candidate recipients comprises at least the one or more entities.

Description

A METHOD AND APPARATUS FOR ACQUAINTANCE MANAGEMENT

AND PRIVACY PROTECTION

FIELD OF THE INVENTION

The present invention generally relates to social networks. More specifically, the invention relates to a method and apparatus for acquaintance management and privacy protection.

BACKGROUND

The modern communications era has brought about a tremendous expansion of communication networks. Communication service providers and device manufacturers are continually challenged to deliver value and convenience to consumers by, for example, providing compelling network services, applications, and content. The developments of communication technologies have contributed to an insatiable desire for new functionality. One area of interest is the development of services and technologies for sharing user data. In data sharing services, people can share posts, photos and so on with others on social networks. Currently, data sharing is mostly public and group-based, with groups being pre-defined in a social network by a user. However, it is time consuming to decide who to share the post with (for example, in case of a photo, it is needed to remember who are in the photo and if they have a social networking account and then tag them so you can remember who they are), so usually people just post as public, regardless of privacy of those people who are closely relevant to the data (such as people in the photo). Although data also may be shared among members of a group, it is a tedious and time consuming process since the group needs to be pre-defined by a user and the user needs to manually add members to the group so it can be used again. Thus, it is desirable to design a privacy-preserving dynamic group formation mechanism. It is getting even valuable but challenging when dealing with a large number of surface acquaintances who are neither friends nor strangers for a user planning to share data in social networks.

SUMMARY

The present description introduces a solution of acquaintance management and privacy protection in a social network. With this solution, some individual persons and/or groups can be identified and suggested in a list of candidate recipients of a post, for example, when the post is to be shared to a social networking site. The proposed solution of acquaintance management and privacy-preserving dynamic group formation also can be used to automatically classify people into groups and record acquaintances for memory recall later.

According to a first aspect of the present invention, there is provided a method comprising: obtaining user data for sharing on a social network from a first user; performing an analysis on the user data to identify one or more entities associated with the user data in the social network, wherein the one or more entities comprise at least one user, at least one group, or a combination thereof; and suggesting to the first user a list of candidate recipients with which the user data is to be shared, wherein the list of candidate recipients comprises at least the one or more entities.

According to a second aspect of the present invention, there is provided an apparatus comprising: at least one processor; and at least one memory comprising computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following: obtaining user data for sharing on a social network from a first user; performing an analysis on the user data to identify one or more entities associated with the user data in the social network, wherein the one or more entities comprise at least one user, at least one group, or a combination thereof; and suggesting to the first user a list of candidate recipients with which the user data is to be shared, wherein the list of candidate recipients comprises at least the one or more entities.

According to a third aspect of the present invention, there is provided a computer program product comprising a computer-readable medium bearing computer program code embodied therein for use with a computer, the computer program code comprising: code for obtaining user data for sharing on a social network from a first user; code for performing an analysis on the user data to identify one or more entities associated with the user data in the social network, wherein the one or more entities comprise at least one user, at least one group, or a combination thereof; and code for suggesting to the first user a list of candidate recipients with which the user data is to be shared, wherein the list of candidate recipients comprises at least the one or more entities.

According to a fourth aspect of the present invention, there is provided an apparatus comprising: obtaining means for obtaining user data for sharing on a social network from a first user; performing means for performing an analysis on the user data to identify one or more entities associated with the user data in the social network, wherein the one or more entities comprise at least one user, at least one group, or a combination thereof; and suggesting means for suggesting to the first user a list of candidate recipients with which the user data is to be shared, wherein the list of candidate recipients comprises at least the one or more entities.

According to a fifth aspect of the present invention, there is provided a method comprising: facilitating access to at least one interface configured to allow access to at least one service, the at least one service configured to at least perform the method in the first aspect of the present invention.

According to exemplary embodiments, sharing of the user data may be based at least in part on privacy settings of at least one of the one or more entities, and wherein said sharing of the user data may comprise at least one of the following: initial sharing of the user data by the first user, and re-sharing of the user data by a recipient of the user data. In an exemplary embodiment, the analysis on the user data may comprise: a content analysis, an object analysis, a context analysis, or a combination thereof. For example, the one or more entities associated with the user data may be identified by: searching social information stored for the social network based at least in part on a result of the performed analysis, wherein the social information may comprise content information, object information, context information or a combination thereof and be associated with one or more users, one or more groups, or a combination thereof within the social network; and determining the one or more entities from the one or more users, the one or more groups, or the combination thereof, according to a matching criterion defined for the social information and the result of the performed analysis. In an exemplary embodiment, the result of the performed analysis and its association with the first user and the one or more entities may be stored for updating the social information.

In accordance with exemplary embodiments, at least one second user from the one or more entities may be presented to the first user as a candidate member of at least one group which comprises a new user-defined group or an existing user-defined group for the first user. For example, the one or more entities may comprise at least one member of an existing user-defined group for the first user. In case that the at least one second user is absent from the existing user-defined group, said presenting may comprise presenting the at least one second user to the first user as a candidate member of the existing user-defined group for the first user.

According to exemplary embodiments, respective acquaintance groups may be maintained for members of the social network comprising at least the first user, by recording one or more acquaintances of a corresponding member of the social network and their respective relationships, and wherein the one or more acquaintances comprise at least one person having ephemeral interactions with the corresponding member of the social network. In an exemplary embodiment, an acquaintance group for the first user may be updated automatically based at least in part of a result of the performed analysis on the user data, wherein the one or more entities comprise at least one acquaintance of the first user. In case that the at least one acquaintance of the first user is absent from the acquaintance group for the first user, said updating may comprise: adding the at least one acquaintance of the first user to the acquaintance group for the first user; and setting a link for the at least one acquaintance of the first user, wherein the link indicates a relationship between the first user and the at least one acquaintance of the first user based at least in part of the result of the performed analysis. In case that the at least one acquaintance of the first user is present in the acquaintance group for the first user, said updating may comprise: setting a new link for the at least one acquaintance of the first user, wherein the new link indicates a relationship between the first user and the at least one acquaintance of the first user based at least in part of the result of the performed analysis. Accordingly, an acquaintance group for the at least one acquaintance of the first user may be updated adaptively by indicating a relationship between the first user and the at least one acquaintance of the first user based at least in part of the result of the performed analysis.

Similarly, an acquaintance group for at least one user of the one or more entities which has at least one acquaintance among the one or more entities may be updated automatically based at least in part of a result of the performed analysis on the user data of the first user. In an exemplary embodiment, an acquaintance group for at least one user of the first user and the one or more entities may be updated automatically based at least in part of a result of the performed analysis, in response to identification of a third user associated with the user data by at least one recipient of the user data, and wherein the third user is an acquaintance of the at least one user of the first user and the one or more entities.

In accordance with exemplary embodiments, the first user may be allowed to modify at least one of the following: selection of one or more recipients of the user data; selection of one or more members of at least one user-defined group for the first user; and respective records of one or more acquaintances of the first user.

In exemplary embodiments of the present invention, the provided methods, apparatus, and computer program products can enable dynamic social group formation and identification through sharing user data, and efficiently manage an acquaintance group for a user with least efforts. For example, for a user planning to share data on a social network, relevant people to share the data with may be suggested to this user with a certain guarantee of privacy. Particularly, a user-defined group and/or an acquaintance group for the user may be dynamically updated and saved for future use, which enriches social information and provides fully serendipitous user experiences.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention itself, the preferable mode of use and further objectives are best understood by reference to the following detailed description of the embodiments when read in conjunction with the accompanying drawings, in which:

Fig.l is a flowchart illustrating a method for acquaintance management and privacy protection in a social network, in accordance with embodiments of the present invention;

Fig.2 shows an exemplary user interface of a post to a social network in accordance with an embodiment of the present invention;

Fig.3 illustrates an exemplary analysis performed on the post shown in Fig.2, in accordance with an embodiment of the present invention;

Fig.4 shows an exemplary user interface of suggesting people to share a post with, in accordance with an embodiment of the present invention; Fig.5 shows an exemplary user interface of creating dynamic groups from suggested people in accordance with an embodiment of the present invention; and

Fig.6 shows an exemplary user interface of showing an acquaintance process between two persons in accordance with an embodiment of the present invention; and

Fig.7 is a simplified block diagram of various apparatuses which are suitable for use in practicing exemplary embodiments of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

The embodiments of the present invention are described in detail with reference to the accompanying drawings. Reference throughout this specification to features, advantages, or similar language does not imply that all of the features and advantages that may be realized with the present invention should be or are in any single embodiment of the invention. Rather, language referring to the features and advantages is understood to mean that a specific feature, advantage, or characteristic described in connection with an embodiment is included in at least one embodiment of the present invention. Furthermore, the described features, advantages, and characteristics of the invention may be combined in any suitable manner in one or more embodiments. One skilled in the relevant art will recognize that the invention may be practiced without one or more of the specific features or advantages of a particular embodiment. In other instances, additional features and advantages may be recognized in certain embodiments that may not be present in all embodiments of the invention.

People normally have three kinds of groups in their social connections. The first kind of group comprises friends who you want to keep constant communications (for example, "Friend Group" in a social network such as Facebook). The second kind of group comprises acquaintances (or surface acquaintances) which you have ephemeral interactions with and want to keep in memory (for example, peers meeting in conferences, persons you met during your holiday trip or anyone you have interacted with). The third kind of group comprises strangers who you do not know at all. In general, one can simply place people as acquaintances/surface acquaintances if you know them but could not treat them as friends so far. As known, everyone may have a large number of acquaintances, but it is difficult to manage that information. For example, Alice may meet many people and take a group photo in a conference, but it is hard to remember each of them and a particular story behind how Alice met them. Smart management of surface acquaintances would offer a great user experience value, in terms of saving tedious information collection and update, but has been less addressed so far.

On the other hand, social networks are getting very crowded in Internet services, both in research and business. People can share posts, photos and the like with others on social networks, in a public or group-based manner. Current social networks primarily manage friends, but not acquaintances. Generally, a user has to manually create a group of friends which may receive an invitation or notification from the user, and thus group formation is explicit. When uploading a new post to a social network, the user planning to share this post on the social network may have to make many decisions on: "Whom I share this post to?", "What is this post about?", "Who would like this?", "Who is this person in the photo?', "Which groups may I send this to?" and so on. The situation when dealing with a large number of surface acquaintances would become worse. Then, it is likely for this user to post as public for saving trouble.

According to exemplary embodiments, a novel solution is proposed for acquaintance management and privacy protection in a social network, which can offer a great user experience by smart management of social information with least efforts. The proposed solution makes it possible to identify a contextual person or group from user data such as a post to be shared by a user, and reuse this group identified from the post to make it from temporal to persistent. For example, the user can send other posts to this group in the future and update this group or create a new group with information collected from the other posts. An approach of implicit group formation is described in accordance with exemplary embodiments, where one or more users, one or more groups, or a combination thereof can be automatically inferred from contents, contexts and/or objects of the user data to be shared, for example through keywords search, face recognition, object detection, acquaintance discovery and the like. This is helpful for a user to quickly determine proper recipients of the shared data, easily remember those persons he/she met and contexts of where they met, and particularly useful for a User Equipment (UE) such as a mobile phone with a small touch screen for which it is difficult to input texts. More details of the proposed solution will be illustrated hereinafter by way of example with reference to the accompanying drawings.

Fig.l is a flowchart illustrating a method for acquaintance management and privacy protection in a social network, in accordance with embodiments of the present invention. It is contemplated that the method described herein may be used with any apparatus connected to a communication network, such as a UE operated by an individual person or an organization of several persons. The UE may be any type of mobile terminal, fixed terminal, or portable terminal comprising a mobile handset, station, unit, device, multimedia computer, multimedia tablet, Internet node, communicator, desktop computer, laptop computer, notebook computer, netbook computer, tablet computer, personal communication system (PCS) device, personal navigation device, personal digital assistants (PDAs), audio/video player, digital camera/camcorder, positioning device, television receiver, radio broadcast receiver, electronic book device, game device, or any combination thereof, comprising the accessories and peripherals of these devices, or any combination thereof.

Additionally or alternatively, it is also contemplated that the method described herein may be used with any apparatus providing or supporting social networking services through a communication network, such as a network node operated by services providers or network operators. The network node may be any type of network device comprising Base Station (BS), Access Point (AP), server, control center, service platform, or any combination thereof. In an exemplary embodiment, the method may be implemented by processes executing on various apparatuses which communicate using an interactive model (such as a client-server model) of network communications. For example, the proposed solution may be performed at a UE, a network node, or both of them through communication interactions for social networking services.

According to exemplary embodiments, the method illustrated with respect to Fig.l enables a social network to have no requirement on a user to explicitly specify respective names of one or more other users and categorize them into corresponding groups. Suggestion of a name list and categorization of candidate group members may be performed in response to sharing of user data on the social network. As shown in block 102 of Fig.l, user data for sharing on a social network may be obtained from a first user. For example, as used herein, the exchangeable terms "user data" and "post" refer to any data that can be represented in machine-readable form, including data that can be used to present content for observation by a human, such as photo, text, audio, music, image, video, thumbnail representation of a larger image, game, graph, table, map, diagram, document, publication and/or spreadsheet, among others. In an example, the first user has a photo and wants to share it on the social network through uploading it as a post to the social network.

Fig.2 shows an exemplary user interface of a post to a social network in accordance with an embodiment of the present invention. As shown in Fig.2, the first user (such as Alice) may select an option (such as an option of "Upload photos" in Fig.2) for uploading a post (such as a photo) to share it on the social network. The photo may be taken previously or at the time of uploading. Optionally, the first user may select an option of "Add my location" to indicate a location at which the photo is taken, or his/her current location when uploading the photo. The options of "Upload photos", "Add my location" and "Suggest people to share with" may be of a button, an icon or any other suitable forms. Additionally or alternatively, the first user may enter some captions or descriptive contents (such as sentences, phrases, keywords and/or the like) related to the post through the user interface. For example, the first user may enter the expression of "Enjoying the best Peking roast duck in Beijing for January monthly dinner - at Da Dong Restaurant, Qianmen, Beijing" to describe what the people in the photo are doing, as shown in Fig.2.

Referring back to Fig.l, in block 104, an analysis may be performed on the user data to identify one or more entities associated with the user data in the social network, wherein the one or more entities may comprise at least one user, at least one group, or a combination thereof. For example, as used herein, a user represents an individual person or an organization of several persons, and a group is a collection of one or more user members which may be dynamically changed due to system update and/or user management. The users or group members among the one or more entities associated with the user data may comprise friends and/or acquaintances of the first user. Optionally, the users or group members among the one or more entities associated with the user data may comprise members and/or nonmembers of the social network. For example, a member of the social network may refer to a user joining the social network and having a user account for the social network.

According to exemplary embodiments, the analysis may comprise a content analysis, an object analysis, a context analysis, or a combination thereof. The content analysis may comprise identifying one or more keywords from the user data such as a text, a document, or any description of the uploaded post. The context analysis may comprise extracting at least one of time, location and activity of the user data. For example, the time of a post may be extracted from post semantics by timestamp or time metadata. The location of a post may be extracted from post semantics or by location identifiers (such as Global Positioning System (GPS) or text inserted from Location-Based Service (LBS) applications). The activity of the post may be extracted from post semantics by using any of those known, developing or future activity classification algorithms. The object analysis may comprise recognizing at least one of object, place and person from the user data. For example, one or more items related to the post may be identified through an object analysis, and some known, developing or future object recognition algorithms can be used to determine whether there is at least one of object, person and place in the post. Particularly, if the post comprises a photo of a person, a suitable face recognition algorithm may be used to identify this person, and optionally the identified person may be suggested as a candidate recipient with which the post is to be shared.

According to an exemplary embodiment, the one or more entities associated with the user data in block 104 may be identified by: searching social information stored for the social network based at least in part on a result of the performed analysis, where the social information may comprise content information, object information, context information or a combination thereof and may be associated with one or more users, one or more groups, or a combination thereof within the social network; and determining the one or more entities from the one or more users, the one or more groups, or the combination thereof, according to a matching criterion defined for the social information and the result of the performed analysis.

Considering complexity, accuracy and/or cost of the implementation, the matching criterion defined for the social information and the result of the performed analysis may be a default criterion or set by the first user manually. In accordance with exemplary embodiments, the social information stored for the social network may comprise personal information related to members and/or nonmembers of the social network. Optionally, such personal information may be contributed by one or more users as the members of the social network. Through matching or comparison between the social information stored for the social network and the result of the performed analysis on the user data to be shared, answers to such questions as "What is this post about?", "Who would like this?", "Who is this person in the photo?", "Which groups may I send this to?" and/or the like can be determined with a little or even no interaction with the first user. The social information for the social network can be stored locally in a memory of an apparatus performing the proposed method, or at a database accessible by the apparatus performing the proposed method. In an exemplary embodiment, the result of the performed analysis in block 104 and its association with the first user and the one or more identified entities may be stored for updating the social information. For example, the association between the result of the performed analysis with the first user and the one or more identified entities may indicate that the first user and the one or more identified entities are involved in an event or activity related to the shared user data such as a photo, a video, a document and so on. Such information may be useful for determination of persons, objects, events, activities and/or so on related to another post uploaded to the social network in the future.

Fig.3 illustrates an exemplary analysis performed on the post shown in Fig.2, in accordance with an embodiment of the present invention. As shown in Fig.3, the object analysis identifies from the uploaded photo that the object in the photo is

Peking duck and that the place is a restaurant (for example, from the behavior of people sitting together in a circular table with food) through image recognition. As an example, an accelerometer in a UE (such as a mobile phone) may be used to detect the behavior of sitting down. The persons in the photo also can be identified with a suitable face recognition algorithm in the object analysis (not shown in Fig.3).

Additionally or alternatively, the context analysis can identify that the photo was taken at 7 PM and the place is Da Dong Restaurant in Qianmen, Beijing, for example, from the location metadata attached to the photo and by using a map application. In an exemplary embodiment, a time or clock application installed in a UE may be used to detect that it is 7 PM. Optionally, a GPS and/or map database may be used to indicate that the location is Da Dong Restaurant in Qianmen, Beijing, for example, when the option of "Add my location" in Fig.2 is selected. As such, the context analysis and the object analysis can help to infer or identify that the activity related to the post is a dinner having Peking duck, as illustrated in Fig.3. Additionally or alternatively, a user as a poster also can manually enter some descriptions of a post (not shown in Fig.3), for example, tagging persons, objects, time and/or events in the post with certain notations. In this case, the content analysis can be used to identify keywords (such as names, titles, addresses, numbers and/or the like) associated with persons, objects, time and/or events in the post from the entered descriptions. In accordance with exemplary embodiments, a list of possible candidates to share the post with can be obtained by combining keyword, time, location, activity, object, place and/or the like and then searching matched information in the user's social network. Optionally, name disambiguation may be performed to find and avoid repeated emergence of the same person/group in the list of possible candidates.

Referring back to Fig.l, in block 106, a list of candidate recipients with which the user data is to be shared is suggested to the first user, wherein the list of candidate recipients comprises at least the one or more entities. As described previously, the one or more entities identified in the social network may comprise at least one user, at least one group comprising one or more members, or a combination thereof. It is realized that the first user may be excluded and not considered as a candidate recipient of the user data even if he/she is also identified from the user data.

Optionally, the list of candidate recipients may further comprise one or more other users/groups specified by the first user in advance. It will be appreciated that the first user such as a poster can specify one or more other users/groups by adding them into the suggested list of candidate recipients. A user (either an individual person/organization or a member of a group) occurring in the list of candidate recipients may comprise a social network member which has a user account in the social network, or a nonmember of the social network. The information regarding the nonmember of the social network may be entered or recorded by a social network member, for example through sharing a post, or tagging a person when receiving a shared post. In an exemplary embodiment, if a person suggested in the list of candidate recipients is not in the social network, a friend request and optionally a reason (such as due to content similarity, co-presence, same activity, appearing in the photo, and/or the like) may be sent to that person, for example via a message or email.

Fig.4 shows an exemplary user interface of suggesting people to share a post with, in accordance with an embodiment of the present invention. Although various embodiments are described with respect to sharing a photo on a social network, as shown in Figs.2-4, it is contemplated that the solution described herein may be applied with any other type of user data shared on the social network, such as text, audio, music, video, table, document and so on. For a photo of people having dinner together, as illustrated with respect to Fig.2, a suitable face recognition algorithm or technology may be used in the object analysis on this photo to identify those people appearing in the photo, for example, if they also have their faces recognized in a social network site from previous photos, or if there is some associated social information regarding their facial features stored at the social network site. In an exemplary embodiment, those people identified in the photo comprise recipients with which the poster would want to share the post, which are marked as Sharon, Bob, Danny, Amelia, Helen, Andrew, Michelle and Liz in Fig.4, since they attended the activity related to the photo. Additionally or alternatively, the people suggested to the poster also can be identified from the content analysis and/or the context analysis, as illustrated with respect to Fig.3. According to exemplary embodiments, other entities (for example, an individual person such as "Amy" and "Max", and a group named as "Monthly dinner group", as shown in Fig.4) not appearing in the photo also may be identified through the analysis described with respect to block 104 in Fig.l. The names or indicators of those identified persons and the other entities may be presented to the poster through the user interface, for example, in response to selecting an option of "Suggest people to share with" as shown in Fig.4. Then the poster can choose one or more proper recipients from a list of the presented candidates.

In accordance with an exemplary embodiment, sharing of the user data may be based at least in part on privacy settings of at least one of the one or more entities as identified in block 104 of Fig.l, considering privacy protection. The sharing of the user data may comprise at least one of the following: initial sharing of the user data by the first user as a poster, and re-sharing of the user data by a recipient of the user data. The at least one of the one or more entities may comprise an entity closely associated with the user data to be shared, such as a person in a photo, a person/organization whose name appears in a document, and so on. According to an exemplary embodiment, an entity (such as a user or a group) can specify privacy settings in its profile, which indicate whether a post is allowed to be shared to others if the entity is closely associated with the post (such as being tagged in the post), or whether the sharing of the post needs to have an approval of the entity. For example, all or part of users in the photo may be checked for their respective privacy settings to determine whether they allow others to see them in this photo and whether this photo can be shared to others. If this is not specified in the privacy settings or the user specifies "approval needed", then a query message may be sent to get the user's approval. This ensures privacy of the shared post. Optionally, the first user as the poster also can share the photo with others not in the photo. In this case, a strict privacy protection is that the sharing may have to be approved by all people in the photo. In an exemplary embodiment, recipients of the shared post are allowed to re-share the received post with others like friends or other groups, if all or part of people tagged in the post approve it. For example, when a recipient begins to re-share the received photo with others, a message may be sent to all or part of people tagged in the photo to see if it is ok to be shared. If so, then the photo may be re-shared. If not, the photo may not be re- shared. When sharing a post, a poster or a recipient also can designate, temporarily or through his/her privacy settings, who may view the post. For example, the poster or the recipient can specify a global policy for all posts, which may be the default privacy settings for sharing, such as public, friends only, acquaintances, specific users, specific groups or the like.

According to exemplary embodiments, the method described with respect to Fig.l may further comprise: presenting at least one second user from the one or more entities to the first user as a candidate member of at least one group which comprises a new user-defined group or an existing user-defined group for the first user. The at least one second user may comprise a friend or an acquaintance of the first user. For example, the one or more entities may comprise at least one member of an existing user-defined group for the first user, and the at least one second user is absent from the existing user-defined group. In this case, said presenting at least one second user from the one or more entities to the first user may comprise presenting the at least one second user to the first user as a candidate member of the existing user-defined group for the first user. From group formation of a list of candidates, similar users may be clustered together (for example, based at least in part on similar interest, attended the same activity, and etc.) into a dynamic group which can be stored in a memory or a database of the social network for future use.

Fig.5 shows an exemplary user interface of creating dynamic groups from suggested people in accordance with an embodiment of the present invention. After a post is submitted to a social network and shared with those recipients chosen by the first user, one or more dynamic groups for the first user may be formed for example through presenting one or more second users among the entities identified from the post (such as those users who are in the photo) to the first user for adding into the respective dynamic groups. For example, as shown in Fig.5, those second users such as Sharon, Bob, Danny, Amelia, Helen, Andrew, Michelle, Liz who are in the photo may be added to a new user-defined group for the first user (such as "January monthly dinner group" which is associated with a current post), and/or an existing user-defined group for the first user (such as "Monthly dinner group" which is already created by the first user for example due to a previous post). In an exemplary embodiment, the first user can modify a name of his/her dynamic group. Additionally or alternatively, the first user can add and/or remove group members manually. The created group, optionally as well as its related social information, may be persisted in a memory for a system performing the proposed solution. In an exemplary embodiment, social information related to a user-defined group for the first user may be shared to all or part of entities within the social network, for example, in a process of searching social information matched with a result of performed analysis on user data shared by another user as illustrated with respect to Fig.l. It is noted that sharing of the social information related to the user-defined group for the first user within the social network would not reveal any personal information of the first user to others. For example, when the social information related to "January monthly dinner group" defined for the first user is utilized in a process of matching content/context/object analysis results from user data of other user, the other user would not aware of that "January monthly dinner group" is defined for the first user.

For a conventional social network such as Facebook, all features are generally originated by online activities and manual check in. Particularly, the conventional social network only records online interactions and things in common between two persons only if they are friends but not acquaintances, because the conventional social network needs persons to be friends before anything can be shared among them.

The proposed solution in accordance with exemplary embodiments can intelligently use the content analysis, the context analysis and/or the object analysis along with a novel social network to automatically suggest relevant recipients with which a post may be shared. Moreover, in accordance with exemplary embodiments, those categorized users in the social network with the proposed solution may comprise not only friends, but also acquaintances. As used herein, acquaintances or surface acquaintances refer to persons who have ephemeral interactions with each other. Thus, in addition to a user's friends and their online activities, the proposed solution also records the user's acquaintances as well as any offline activities or interactions between them, such as from the same photo, from common activities, having the same or similar interests, and/or the like.

Fig.6 shows an exemplary user interface of showing an acquaintance process between two persons in accordance with an embodiment of the present invention. The acquaintance process may comprise one or more offline activities or interactions between two acquaintances. According to exemplary embodiments, respective acquaintance groups may be maintained for members of the social network comprising at least the first user (such as a poster), by recording one or more acquaintances of a corresponding member of the social network and their respective relationships, where the one or more acquaintances may comprise at least one person having ephemeral interactions with the corresponding member of the social network.

For example, in case that the one or more entities identified in block 104 of Fig.l comprise at least one acquaintance of the first user, the method described with respect to Fig.l may further comprise: updating an acquaintance group for the first user automatically based at least in part of a result of the performed analysis on the user data from the first user. For example, if the at least one acquaintance of the first user is absent from the acquaintance group for the first user, then said updating the acquaintance group for the first user may comprise: adding the at least one acquaintance of the first user to the acquaintance group for the first user, and setting a link for the at least one acquaintance of the first user, which indicates a relationship

(such as an acquaintance process) between the first user and the at least one acquaintance of the first user based at least in part of the result of the performed analysis. Alternatively, if the at least one acquaintance of the first user is present in the acquaintance group for the first user, then said updating may comprises: setting a new link for the at least one acquaintance of the first user, which indicates a relationship between the first user and the at least one acquaintance of the first user based at least in part of the result of the performed analysis. Particularly, if the result of the performed analysis on the user data from the first user (such as Alice) shows that the first user and the at least one acquaintance (such as John) of the first user both appear in the user data (such as a video or a photo taken at a CPSCom conference on Nov. 23, 2012), then the link set for the at least one acquaintance and the first user may indicate that they met due to an event or activity associated with the user data, for example, "You met John at the CPSCom conference on Nov. 23, 2012" as shown on the user interface for Alice in Fig.6. Similarly, an acquaintance group for the above mentioned at least one acquaintance (such as John) of the first user also can be updated adaptively, for example, by indicating a relationship (such as an acquaintance process) between the first user and the at least one acquaintance of the first user based at least in part of the result of the performed analysis.

Additionally, an acquaintance group for at least one user of the one or more entities which has at least one acquaintance among the one or more entities also can be updated automatically based at least in part of a result of the performed analysis, according to an exemplary embodiment. For example, persons marked in the uploaded photo as shown in Figs. 2-4 can be automatically and selectively (for example, selecting all or only those not friends of the first user yet) categorized into a group of "People I Met" (which also may be regarded as an acquaintance group) for the first user who uploaded the photo, and a link with each person may be labeled such as "January monthly dinner". Similarly, those persons marked in the photo also can be automatically and selectively categorized into respective acquaintance groups for their corresponding acquaintances which are also marked in the photo. As such, the respective relationships between any two acquaintances associated with the user data shared by the first user can be recorded automatically, which may be helpful to remind people how and where they met others. Advantageously, the proposed solution can use these records of offline activities, and manage them automatically by leveraging distributed crowdsourcing and/or algorithms. Regarding privacy, it also can offer an automatic approach (for example considering all or part of users in an activity from a photo, activity, email and etc.) than manual settings from a privacy user interface.

In accordance with exemplary embodiments, a surface acquaintance group for at least one user of the first user and the one or more entities described with respect to the method of Fig.l may be updated automatically based at least in part of a result of the performed analysis on the user data from the first user, in response to identification (such as tagging or marking) of a third user associated with the user data by at least one recipient of the user data, where the third user is a surface acquaintance of the at least one user of the first user and the one or more entities. For example, when others receive a photo shared by Alice, if they are identified or tagged in the photo (either manually or automatically), they may become automatically members of a group classified from the photo and defined for Alice (such as "January monthly dinner group" shown in Fig.5). Optionally, any tagged person in the photo which is an acquaintance with another tagged person in the photo may become a member of a surface acquaintance group maintained for the another tagged person.

However, it is possible that not all persons in the photo are tagged when sharing. In this case, a user receiving the shared photo can tag others in the photo which he/she knows. As an example, the tagging indicates that the user (such as user A) and the tagged user (such as user B) know each other, so a link may be established with a relationship between user A and user B (such as "A met B from the January monthly dinner group"), and user B can be added to an acquaintance group (such as a group of

"People I Met") maintained for user A. In response to tagging of user B, respective acquaintance groups for other previously tagged users (such as users C and D) in the photo also may be updated by establishing corresponding links which respectively indicate a relationship between user C and user B (such as "C met B from the January monthly dinner group"), and a relationship between user D and user B (such as "D met B from the January monthly dinner group"). The end result is that every user can automatically see how he/she knows another user through his/her social interactions (which may be reflected by the shared post), and optionally view any surface acquaintances in the user interface as shown in Fig.6. According to exemplary embodiments, the first user which shares the user data as described with respect to Figs.1-6 may be allowed to modify at least one of the following: selection of one or more recipients of the user data; selection of one or more members of at least one user-defined group for the first user; and respective records of one or more acquaintances of the first user.

The various blocks shown in Fig.l may be viewed as method steps, and/or as operations that result from operation of computer program code, and/or as a plurality of coupled logic circuit elements constructed to carry out the associated function(s). The schematic flow chart diagrams described above are generally set forth as logical flow chart diagrams. As such, the depicted order and labeled steps are indicative of specific embodiments of the presented methods. Other steps and methods may be conceived that are equivalent in function, logic, or effect to one or more steps, or portions thereof, of the illustrated methods. Additionally, the order in which a particular method occurs may or may not strictly adhere to the order of the corresponding steps shown.

The proposed solution can create a method and apparatus to identify and suggest one or more users and/or groups as candidate recipients when sharing a post to a social networking site, and optionally to automatically classify those users into respective dynamic groups and record surface acquaintances for memory recall later. For example, when a post pertaining to a photo, a publication or any activity within a certain context of the post is to be shared, the proposed solution can automatically identify or suggest a name list comprising the people to share the post with, and then dynamically save all or part of them into respective groups (for example, people who are my friends, people I know but are not my friends, people associated with an event/activity which comprise my friends and acquaintances, people I do not know, and so on). Thus the dynamic group formation may be implemented through sharing. By identifying and classifying people into respective groups automatically based at least in part on sharing, a user can know his/her relationship with others who are not friends but just surface acquaintances. This is different from those conventional social networks which only records interactions with people who are friends, but not with people who are acquainted with but have not declared friendship.

Here is a use scenario to which the proposed solution may be applied. In this scenario, John attended a workshop and has a group photo on the last day of the workshop. John shared the group photo on a social network according to exemplary embodiments, and some of his friends identified and manually marked person names next to heads in the photo (for example, a suitable face recommendation algorithm also can do it automatically). Then John's acquaintance group can be automatically updated with those persons whose photo heads have been marked with all or part of contexts/backgrounds from the photo. A few years later, John can browse or search those moments and find those conference peers in memory, which is very rich timeline information. John also can convert some members from his acquaintance group into a friend group. It is noted that there is no need for John to take any action for adding those acquaintances into his acquaintance group, which would be very hard for him due to a large amount of social events. Those works may be primarily done by other persons who know those acquaintances or treat those acquaintances as their individual friends. It would be a fully serendipitous experience when John browses his acquaintance group timeline to find out people he met from before, which may be a great surprise for John. It may be easy to extend such experience beyond a photo, such as an email with several links, and so on. Those acquaintances information derived from sharing and/or re-sharing the post of John also can be maintained for others associated or not associated with the post, which facilitates acquaintances information utilization and forms a social circle of all persons which a user knows. Regarding to social circle formation, a crowdsourcing approach (in which everyone can contribute for those persons they may be familiar with from a group photo, for example, to get precise and rich information in the collaborative and distributed way), as well as an online/offline or cyber/physical approach (in which a personal relationship can be linked by an offline/physical event, such as conference, party, activity and the like marked by a post caption or context) may be employed by the proposed solution. It can enhance the social coverage and provide serendipitous user experiences. Regarding to dynamical group formation, the proposed solution can recommend an event-based or context-aware dynamic group as candidate recipients when a user plans to share a post. It can improve the relevancy of recipients of the shared post while keeping the privacy in a right social circle.

Many advantages can be achieved by using the solution provided by the present invention. For example, the proposed method can suggest relevant people to share a post with, by intelligently using at least one of content, context and object recognition along with a social network, and can dynamically form respective groups to save for future use in the social network. It enables the privacy by ensuring that only permitted people can view and share posts. Particularly, no one else in a group knows that they are part of this group because each person in the group just receives the shared content, without knowing who else this content was shared with.

Acquaintance (or surface acquaintance) groups also can be efficiently managed with least efforts, which may enrich social network experiences since a user having a large number of surface acquaintances can dynamically see those persons he/she has encountered, met and know without much effort. The proposed solution also can offer rich social information and serendipitous user experiences, while keeping friend groups focused, since one has more choices to arrange a person in a friend group, an acquaintance group, or a group comprising friends and acquaintances.

Fig.7 is a simplified block diagram of various apparatuses which are suitable for use in practicing exemplary embodiments of the present invention. In Fig.7, a UE 710

(such as mobile phone, wireless terminal, portable device, PDA, multimedia tablet, desktop computer, laptop computer and etc.) may be adapted for communicating with a network node 720 (such as a server, an AP, a BS, a control center, a service platform and etc.). In an exemplary embodiment, the UE 710 may comprise at least one processor (such as a data processor (DP) 71 OA shown in Fig.7), and at least one memory (such as a memory (MEM) 71 OB shown in Fig.7) comprising computer program code (such as a program (PROG) 710C shown in Fig.7). The at least one memory and the computer program code may be configured to, with the at least one processor, cause the UE 710 to perform operations and/or functions described in combination with Figs.1-6. In an exemplary embodiment, the UE 710 may optionally comprise a suitable transceiver 710D for communicating with an apparatus such as another UE, a network node (such as the network node 720) and so on. The network node 720 may comprise at least one processor (such as a data processor (DP) 720A shown in Fig.7), and at least one memory (such as a memory (MEM) 720B shown in

Fig.7) comprising computer program code (such as a program (PROG) 720C shown in Fig.7). The at least one memory and the computer program code may be configured to, with the at least one processor, cause the network node 720 to perform operations and/or functions described in combination with Figs.1-6. In an exemplary embodiment, the network node 720 may optionally comprise a suitable transceiver

720D for communicating with an apparatus such as another network node, a UE

(such as UE 710) or other network entity (not shown in Fig.7). For example, at least one of the transceivers 710D, 720D may be an integrated component for transmitting and/or receiving signals and messages. Alternatively, at least one of the transceivers

710D, 720D may comprise separate components to support transmitting and receiving signals/messages, respectively. The respective DPs 71 OA and 720A may be used for processing these signals and messages.

Alternatively or additionally, the UE 710 and the network node 720 may comprise various means and/or components for implementing functions of the foregoing method steps described with respect to Figs.1-6. According to exemplary embodiments, an apparatus (such as a first user's UE 710, or the network node 720 communicating with a UE of the first user) may comprise: obtaining means for obtaining user data for sharing on a social network from the first user; performing means for performing an analysis on the user data to identify one or more entities associated with the user data in the social network, wherein the one or more entities comprise at least one user, at least one group, or a combination thereof; and suggesting means for suggesting to the first user a list of candidate recipients with which the user data is to be shared, wherein the list of candidate recipients comprises at least the one or more entities. Optionally, the apparatus may further comprise: presenting means for presenting at least one second user from the one or more entities to the first user as a candidate member of at least one group which comprises a new user-defined group or an existing user-defined group for the first user; and/or updating means for updating an acquaintance group for the first user automatically based at least in part of a result of the performed analysis, wherein the one or more entities comprise at least one acquaintance of the first user. Alternatively, the above mentioned obtaining means, performing means, suggesting means, presenting means and updating means may be implemented at either the UE 710 or the network node 720, or at both of them in a distributed manner. In an exemplary embodiment, a solution providing for the UE 710 and the network node 720 may comprise facilitating access to at least one interface configured to allow access to at least one service, and the at least one service may be configured to at least perform functions of the foregoing method steps as described with respect to Figs.1-6.

At least one of the PROGs 7 IOC and 720C is assumed to comprise program instructions that, when executed by the associated DP, enable an apparatus to operate in accordance with the exemplary embodiments, as discussed above. That is, the exemplary embodiments of the present invention may be implemented at least in part by computer software executable by the DP 71 OA of the UE 710 and by the DP 720 A of the network node 720, or by hardware, or by a combination of software and hardware.

The MEMs 71 OB and 720B may be of any type suitable to the local technical environment and may be implemented using any suitable data storage technology, such as semiconductor based memory devices, flash memory, magnetic memory devices and systems, optical memory devices and systems, fixed memory and removable memory. The DPs 71 OA and 720A may be of any type suitable to the local technical environment, and may comprise one or more of general purpose computers, special purpose computers, microprocessors, digital signal processors (DSPs) and processors based on multi-core processor architectures, as non-limiting examples.

In general, the various exemplary embodiments may be implemented in hardware or special purpose circuits, software, logic or any combination thereof. For example, some aspects may be implemented in hardware, while other aspects may be implemented in firmware or software which may be executed by a controller, microprocessor or other computing device, although the invention is not limited thereto. While various aspects of the exemplary embodiments of this invention may be illustrated and described as block diagrams, flow charts, or using some other pictorial representation, it is well understood that these blocks, apparatus, systems, techniques or methods described herein may be implemented in, as non-limiting examples, hardware, software, firmware, special purpose circuits or logic, general purpose hardware or controller or other computing devices, or some combination thereof.

It will be appreciated that at least some aspects of the exemplary embodiments of the inventions may be embodied in computer-executable instructions, such as in one or more program modules, executed by one or more computers or other devices. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types when executed by a processor in a computer or other device. The computer executable instructions may be stored on a computer readable medium such as a hard disk, optical disk, removable storage media, solid state memory, random access memory (RAM), and etc. As will be realized by one of skill in the art, the functionality of the program modules may be combined or distributed as desired in various embodiments. In addition, the functionality may be embodied in whole or in part in firmware or hardware equivalents such as integrated circuits, field programmable gate arrays (FPGA), and the like.

Although specific embodiments of the invention have been disclosed, those having ordinary skill in the art will understand that changes can be made to the specific embodiments without departing from the spirit and scope of the invention. The scope of the invention is not to be restricted therefore to the specific embodiments, and it is intended that the appended claims cover any and all such applications, modifications, and embodiments within the scope of the present invention.

Claims

CLAIMS What is claimed is:

1. A method comprising:

obtaining user data for sharing on a social network from a first user;

performing an analysis on the user data to identify one or more entities associated with the user data in the social network, wherein the one or more entities comprise at least one user, at least one group, or a combination thereof; and

suggesting to the first user a list of candidate recipients with which the user data is to be shared, wherein the list of candidate recipients comprises at least the one or more entities.

2. The method according to claim 1, wherein the analysis comprises: a content analysis, an object analysis, a context analysis, or a combination thereof.

3. The method according to claim 1 or 2, wherein sharing of the user data is based at least in part on privacy settings of at least one of the one or more entities, and wherein said sharing of the user data comprises at least one of the following:

initial sharing of the user data by the first user, and

re-sharing of the user data by a recipient of the user data.

4. The method according to any one of claims 1 to 3, wherein the one or more entities associated with the user data are identified by:

searching social information stored for the social network based at least in part on a result of the performed analysis, wherein the social information comprises content information, object information, context information or a combination thereof and is associated with one or more users, one or more groups, or a combination thereof within the social network; and

determining the one or more entities from the one or more users, the one or more groups, or the combination thereof, according to a matching criterion defined for the social information and the result of the performed analysis.

5. The method according to claim 4, wherein the result of the performed analysis and its association with the first user and the one or more entities are stored for updating the social information.

6. The method according to any one of claims 1 to 5, further comprising:

presenting at least one second user from the one or more entities to the first user as a candidate member of at least one group which comprises a new user-defined group or an existing user-defined group for the first user.

7. The method according to claim 6, wherein the one or more entities comprise at least one member of an existing user-defined group for the first user, and the at least one second user is absent from the existing user-defined group, and wherein said presenting comprises:

presenting the at least one second user to the first user as a candidate member of the existing user-defined group for the first user.

8. The method according to any one of claims 1 to 7, wherein respective acquaintance groups are maintained for members of the social network comprising at least the first user, by recording one or more acquaintances of a corresponding member of the social network and their respective relationships, and wherein the one or more acquaintances comprise at least one person having ephemeral interactions with the corresponding member of the social network.

9. The method according to claim 8, further comprising:

updating an acquaintance group for the first user automatically based at least in part of a result of the performed analysis, wherein the one or more entities comprise at least one acquaintance of the first user.

10. The method according to claim 9, wherein the at least one acquaintance of the first user is absent from the acquaintance group for the first user, and wherein said updating comprises:

adding the at least one acquaintance of the first user to the acquaintance group for the first user; and

setting a link for the at least one acquaintance of the first user, wherein the link indicates a relationship between the first user and the at least one acquaintance of the first user based at least in part of the result of the performed analysis.

11. The method according to claim 9, wherein the at least one acquaintance of the first user is present in the acquaintance group for the first user, and wherein said updating comprises:

setting a new link for the at least one acquaintance of the first user, wherein the new link indicates a relationship between the first user and the at least one acquaintance of the first user based at least in part of the result of the performed analysis.

12. The method according to any one of claims 9 to 11, wherein an acquaintance group for the at least one acquaintance of the first user is updated adaptively by indicating a relationship between the first user and the at least one acquaintance of the first user based at least in part of the result of the performed analysis.

13. The method according to any one of claims 8 to 12, wherein an acquaintance group for at least one user of the one or more entities which has at least one acquaintance among the one or more entities is updated automatically based at least in part of a result of the performed analysis.

14. The method according to any one of claims 8 to 13, wherein an acquaintance group for at least one user of the first user and the one or more entities is updated automatically based at least in part of a result of the performed analysis, in response to identification of a third user associated with the user data by at least one recipient of the user data, and wherein the third user is an acquaintance of the at least one user of the first user and the one or more entities.

15. The method according to any one of claims 1 to 14, wherein the first user is allowed to modify at least one of the following:

selection of one or more recipients of the user data;

selection of one or more members of at least one user-defined group for the first user; and

respective records of one or more acquaintances of the first user.

16. An apparatus, comprising:

at least one processor; and

at least one memory comprising computer program code,

the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following:

obtaining user data for sharing on a social network from a first user;

performing an analysis on the user data to identify one or more entities associated with the user data in the social network, wherein the one or more entities comprise at least one user, at least one group, or a combination thereof; and suggesting to the first user a list of candidate recipients with which the user data is to be shared, wherein the list of candidate recipients comprises at least the one or more entities.

17. The apparatus according to claim 16, wherein the analysis comprises: a content analysis, an object analysis, a context analysis, or a combination thereof.

18. The apparatus according to claim 16 or 17, wherein sharing of the user data is based at least in part on privacy settings of at least one of the one or more entities, and wherein said sharing of the user data comprises at least one of the following: initial sharing of the user data by the first user, and

re-sharing of the user data by a recipient of the user data.

19. The apparatus according to any one of claims 16 to 18, wherein the one or more entities associated with the user data are identified by:

20. The apparatus according to claim 19, wherein the result of the performed analysis and its association with the first user and the one or more entities are stored for updating the social information.

21. The apparatus according to any one of claims 16 to 20, wherein the apparatus is caused to further perform:

22. The apparatus according to claim 21, wherein the one or more entities comprise at least one member of an existing user-defined group for the first user, and the at least one second user is absent from the existing user-defined group, and wherein said presenting comprises:

23. The apparatus according to any one of claims 16 to 22, wherein respective acquaintance groups are maintained for members of the social network comprising at least the first user, by recording one or more acquaintances of a corresponding member of the social network and their respective relationships, and wherein the one or more acquaintances comprise at least one person having ephemeral interactions with the corresponding member of the social network.

24. The apparatus according to claim 23, wherein the apparatus is caused to further perform:

25. The apparatus according to claim 24, wherein the at least one acquaintance of the first user is absent from the acquaintance group for the first user, and wherein said updating comprises:

26. The apparatus according to claim 24, wherein the at least one acquaintance of the first user is present in the acquaintance group for the first user, and wherein said updating comprises:

27. The apparatus according to any one of claims 24 to 26, wherein an acquaintance group for the at least one acquaintance of the first user is updated adaptively by indicating a relationship between the first user and the at least one acquaintance of the first user based at least in part of the result of the performed analysis.

28. The apparatus according to any one of claims 23 to 27, wherein an acquaintance group for at least one user of the one or more entities which has at least one acquaintance among the one or more entities is updated automatically based at least in part of a result of the performed analysis.

29. The apparatus according to any one of claims 23 to 28, wherein an acquaintance group for at least one user of the first user and the one or more entities is updated automatically based at least in part of a result of the performed analysis, in response to identification of a third user associated with the user data by at least one recipient of the user data, and wherein the third user is an acquaintance of the at least one user of the first user and the one or more entities.

30. The apparatus according to any one of claims 16 to 29, wherein the first user is allowed to modify at least one of the following:

selection of one or more recipients of the user data;

respective records of one or more acquaintances of the first user.

31. A computer program product comprising a computer-readable medium bearing computer program code embodied therein for use with a computer, the computer program code comprising:

code for obtaining user data for sharing on a social network from a first user; code for performing an analysis on the user data to identify one or more entities associated with the user data in the social network, wherein the one or more entities comprise at least one user, at least one group, or a combination thereof; and

code for suggesting to the first user a list of candidate recipients with which the user data is to be shared, wherein the list of candidate recipients comprises at least the one or more entities.

32. The computer program product according to claim 31, wherein the analysis comprises: a content analysis, an object analysis, a context analysis, or a combination thereof.

33. The computer program product according to claim 31 or 32, wherein sharing of the user data is based at least in part on privacy settings of at least one of the one or more entities, and wherein said sharing of the user data comprises at least one of the following:

initial sharing of the user data by the first user, and

re-sharing of the user data by a recipient of the user data.

34. The computer program product according to any one of claims 31 to 33, wherein the one or more entities associated with the user data are identified by:

35. The computer program product according to claim 34, wherein the result of the performed analysis and its association with the first user and the one or more entities are stored for updating the social information.

36. The computer program product according to any one of claims 31 to 35, wherein the computer program code further comprises:

code for presenting at least one second user from the one or more entities to the first user as a candidate member of at least one group which comprises a new user-defined group or an existing user-defined group for the first user.

37. The computer program product according to claim 36, wherein the one or more entities comprise at least one member of an existing user-defined group for the first user, and the at least one second user is absent from the existing user-defined group, and wherein said presenting comprises:

38. The computer program product according to any one of claims 31 to 37, wherein respective acquaintance groups are maintained for members of the social network comprising at least the first user, by recording one or more acquaintances of a corresponding member of the social network and their respective relationships, and wherein the one or more acquaintances comprise at least one person having ephemeral interactions with the corresponding member of the social network.

39. The computer program product according to claim 38, wherein the computer program code further comprises:

code for updating an acquaintance group for the first user automatically based at least in part of a result of the performed analysis, wherein the one or more entities comprise at least one acquaintance of the first user.

40. The computer program product according to claim 39, wherein the at least one acquaintance of the first user is absent from the acquaintance group for the first user, and wherein said updating comprises:

The computer program product according to claim 39, wherein the at least acquaintance of the first user is present in the acquaintance group for the first user, and wherein said updating comprises:

42. The computer program product according to any one of claims 39 to 41, wherein an acquaintance group for the at least one acquaintance of the first user is updated adaptively by indicating a relationship between the first user and the at least one acquaintance of the first user based at least in part of the result of the performed analysis.

43. The computer program product according to any one of claims 38 to 42, wherein an acquaintance group for at least one user of the one or more entities which has at least one acquaintance among the one or more entities is updated automatically based at least in part of a result of the performed analysis.

44. The computer program product according to any one of claims 38 to 43, wherein an acquaintance group for at least one user of the first user and the one or more entities is updated automatically based at least in part of a result of the performed analysis, in response to identification of a third user associated with the user data by at least one recipient of the user data, and wherein the third user is an acquaintance of the at least one user of the first user and the one or more entities.

45. The computer program product according to any one of claims 31 to 44, wherein the first user is allowed to modify at least one of the following:

selection of one or more recipients of the user data; selection of one or more members of at least one user-defined group for the first user; and

respective records of one or more acquaintances of the first user.

46. An apparatus, comprising:

obtaining means for obtaining user data for sharing on a social network from a first user;

performing means for performing an analysis on the user data to identify one or more entities associated with the user data in the social network, wherein the one or more entities comprise at least one user, at least one group, or a combination thereof; and

suggesting means for suggesting to the first user a list of candidate recipients with which the user data is to be shared, wherein the list of candidate recipients comprises at least the one or more entities.

47. A method comprising facilitating access to at least one interface configured to allow access to at least one service, the at least one service configured to at least perform a method of at least one of claims 1 to 15.