KR101616064B1 - Adheat advertisement model for social network - Google Patents

Abstract

In one implementation, a computer implemented method includes receiving at a server information indicating activity levels of social network users that are implemented in the computer, or information indicating the user's personal relationships on the computer-implemented social network . The method further includes generating an influence score for the users based on the received information by the server. The method further comprises transmitting the advertisement from the propagating user to the recipient user when the difference between the first influential score of the propagating user and the second influential score of the receiving user is greater than the threshold value, And cyclically propagating the advertisement to the server via the computer-implemented social network.

Description

{ADHEAT ADVERTISEMENT MODEL FOR SOCIAL NETWORK}

The present description generally describes methods and systems for placing advertisements on a social network.

This disclosure generally relates to providing advertisements to users of social networks. A social network can be an online system that provides a forum where geographically separated users interact with one another. Social networks can be targets in other aspects of social interaction such as friendships and business networking.

Methods of advertising to users of a social network include targeting a user of a social network and a social network with specific content. In some methods, targeting the entire social network with advertisements about the general purpose of the social network (e.g., business). In other methods, particular users have become targets of advertisements based on the content of each of the user's profile pages. For example, if a user discusses a sport on his / her profile page, an advertisement about the sport may target that user.

This specification describes techniques for providing advertisements to users of social networks. In general, the interactions of the viewer with particular advertisements (e.g., interactions in which a user skips ads) may be monitored, and then the system may be able to monitor ads that are likely to be viewed by users and which are less likely to skip May be selected.

In one implementation, a computer implemented method includes receiving, at a server, information indicative of activity levels of social network users implemented in a computer or of the users on the computer-implemented social network . The method includes generating, by the server, influence scores for the users based on the received information. The method also includes receiving an advertisement from the propagating user to the recipient user when a difference between a first influential score of a propagating user and a second influential score of a recipient user is greater than a threshold, And cyclically propagating the advertisement to the server via the computer-implemented social network among users having an acquaintance relationship.

In another implementation, a system for propagating an advertisement to users of a social network comprises: one or more servers; An interface to the one or more servers for receiving information indicative of an activity level of users of the social network or an acquaintance relationship of the users on the social network; Means for generating influence scores for the user based on the received information; And sending an advertisement to the receiving user from the propagating user when the difference between the first influential score of the propagating user and the second influential score of the receiving user is greater than a threshold value, And a cyclic propagation module installed on the one or more servers to cyclically propagate the advertisement through the mobile terminal.

In another implementation, a computer implemented method comprises the steps of: outputting an advertisement to a first user of a computer-implemented social network, said output causing said advertisement to be displayed to said first user; Receiving an input associated with the advertisement from the first user; Retrieving influence scores for the first user and influencing scores for second users of the social network associated with the first user by an acquaintance relationship; And propagating the advertisement to the second users having an impact score less than the impact score for the first user.

The detailed description of one or more embodiments set forth herein is set forth in the accompanying drawings and the description below. Other features, aspects and advantages of the subject matter will become apparent from the description, drawings and claims.

1 is a diagram of an exemplary system for receiving bids for opportunities to advertise to users of a social network and for propagating advertisements from a user to a user via a social network.
Figure 2 is another diagram of an exemplary system for receiving bids for opportunities to advertise to users of a social network and for propagating advertisements from a user to a user via a social network.
3 is a flow chart of an exemplary process for granting an opportunity to display advertisements to users of a social network based on advertiser requests.
4 is a flowchart of each exemplary process for cyclically propagating advertisements through users of a social network.
5 is a flowchart of each exemplary process for generating a user ' s interest model from user generated content.
Figure 6 is a flowchart of each exemplary process that allows an advertiser to participate in bids for opportunities to display advertisements to users of the social network.
7 is a flowchart of each exemplary process for propagating an advertisement from a propagating user to a receiving user.
8 is a schematic diagram of a computer system.
The same reference symbols in the several Figures represent the same elements.

This specification generally describes the placement of advertisements on a social network. More specifically, the specification describes the allocation of opportunities for users to display advertisements and the propagation of advertisements through social networks. In some instances, a method and system is described in which an advertiser can target users of a social network based on the interests of the user and the impact on the social network. The opportunity to display ads to an influential user with interests related to the ad may be more valuable to the advertiser than the opportunity to display the ad to an unaffected user with unrelated interests (or even an unaffected user with relevant interests) have. The user's influence on the social network can be determined by seeing the level of user activity and the acquaintance relationship in the social network. The advertiser may receive a ranked list of anonymous users according to user interests and influences. The bidding mechanism can be used to accommodate a large number of advertisers seeking to have an opportunity to display advertisements to a finite number of users that are relevant and influential on the social network.

In some instances, if an advertiser is presented with an opportunity to display an advertisement to a particular anonymous user, the advertisement from the advertiser is propagated from the user to the user's friends using a heat diffusion model. For example, user influence on a social network can be indicated by hit intensity or hit score, and more influential users have high hit scores. The propagation between the users can then be modeled using a heat diffusion model. For example, if a targeted user of an advertisement has a larger "hit" than a user who has not yet been targeted, the ad may spread (propagate) among the two connected users. This allows ads to be propagated from more influential users to less influential users via the social network. One advantage gained from the described method is the ability of advertisers to maximize advertising efficiency by propagating ads to affected users from influential users.

1 is a diagram of an exemplary system 100 for receiving bids for opportunities to advertise to users of a social network and for propagating advertisements from a user to a user via a social network. The system 100 may include advertisers 102a-102c, a server 112 that has received bids, and a social network 118. [

Advertiser 102a may submit a request to display advertisements 108 to users of the social network with certain features 106. [ The server 112 may receive the request and provide the advertiser 102a with a list of anonymous users that rank user impact scores and / or user similarities to the requested features 114. [ The advertiser 102a may then bid for an opportunity to display the advertisement 108 to one or more ranked users 114. [ The server 112 may receive bids 104b and 104c from a plurality of advertisers 102b and 102c for an opportunity to display an advertisement to any anonymous user 114. [ For example, in the bidding chart 114, there are two bids ($ 1.50 for sports ads and $ 0.60 for music ads) for the opportunity to display advertisements to user U4. The server 112 then gives the highest bidder the opportunity to display the advertisement, and on that occasion the advertisement 116 can be displayed on the social network 118. [

The advertisement may first be displayed to an anonymously bidded user (e.g., user U4 120). The advertisement 116 may then be propagated through the social network 118 in accordance with the connection relationship between the users. For example, an advertisement may propagate from one connected user to another as long as the hit (or influence) score for the propagating user is higher than the hit score for the receiving user. For example, user U4 120 is connected to user U17 122. User U4 has a hit score of 500, and user U17 has a hit score of 450. Since the hit score of U4 is greater than U17, the advertisement can be propagated from user U4 120 to user U17 122. However, since the hit score of U2 of 510 is greater than the hit score of user U4 (114), the advertisement can not be propagated from user U4 120 to user U2 126.

2 is another diagram of an exemplary system 200 for receiving bids for opportunities to advertise to users of a social network and for propagating advertisements from a user to a user via a social network. The system 200 may include a client side 202 and a server side 204. The client side 202 may interact with the advertisers 206 to submit requests and bids to display advertisements to selected users of the social network. In addition, the client side 202 may interact with the users 208 to display, for example, advertisements submitted by the advertiser 206 within a page viewed by users 208 on the social network. The server side 204 receives requests from the advertiser 206 and, through the bidding process, gives the selected users 208 opportunities to display advertisements. The server side 204 may also utilize, for example, a heat spreading model, among users 208 of the social network connected by an acquaintance relationship (e.g., users are designated as friends, or users are visiting other user's profiles, etc.) So that advertisements can be propagated.

The client side 202 may include an advertiser 206 that submits characteristics of users that the advertiser 206 desires to target as an ad. The ad interface referred to herein as adheat interface 210 may receive the features and communicate those characteristics to the server side 204. [ The server side 204 may include a web server 214 that receives the characteristics and may be configured to determine the impact of each user in the social network through the use of the database 216 and the similarity And produces a list of ranked users. After ranking, the web server 214 may, in some implementations, deliver the ranking list to the client side 202.

In some implementations, the web server 214 may create an ordered list of users in response to receiving advertisements and / or the content of the advertisements from the advertiser 206. The sorted list can sort users according to the likelihood of the user accepting the content of the ad and / or the amount of influence the user has on other users of the social network. The users listed near the top of the sorted list are more likely to accept the content of the ad and / or have a greater impact on other users of the social network than the users listed near the bottom of the sorted list .

The ad hoc interface 210 on the client side may receive and provide the advertiser 206 with a ranking list of users. The advertiser 206 may provide the ad hoc interface 210 with a bid for an opportunity to display an advertisement to selected users on the ranking list. Ad hoc interface 210 may forward bids to server side 204. After receiving the bids, the web server 214 may conduct an auction and, based on the bids, give the ranked users an opportunity to display the advertisement. The auction process is described in more detail below.

Web server 214 may send advertisements to client side 202. The gadget 212 at the client side 202 may display to the users 208 the advertisements provided by the advertisers 206 that won the opportunity to be displayed to the users 208. [ The advertisement may then be propagated through the social network described herein using the friend relationship graph 218. This is explained in more detail below.

As described above, the advertiser 206 may provide a request to the ad hoc module 210 as an advertisement target for users of the social network. The request may include information identifying the content of the ad and / or features of the user that the advertiser wishes to target to the ad. User characteristics may include demographic information such as age or age range, gender, interest, occupation, income, educational background, or user's geographic location.

In some instances, the advertiser 206 may provide one or more keywords to the ad hoc module 210 in relation to the users that they wish to target. For example, the advertiser 206 may provide a request to the ad hoc module 210 to display " sports " related advertisements to " male " users having " ages between 18 and 35 years old.

In some implementations, the advertiser 206 may select descriptors for the content of the ad and features of users that the advertiser 206 wants to target the ad from a drop-down menu have. For example, the drop down boxes may suggest to the advertiser a number of user characteristics that can be selected. In some instances, the advertiser may provide the ad itself to the ad hoc module 210, and the ad hoc module 210 may analyze the ad and determine the content of the ad. The ad provided to the ad hoc module 210 may be text, image, video, or a combination thereof.

The ad hoc module 210 may determine the content of the ad using a content modeling method that may be used to derive the content of the ad based on the words or symbols used in and / do. In some instances, the content of the ad may be derived from the text of the ad. If text or video is provided with the advertisement, the text for the advertisement can be created using optical character recognition. In some instances, the content of the advertisement may be derived from meta information associated with the advertisement.

The ad hoc module 210 may submit a request from the advertiser 206 to the web server 214. In response, the web server 214 may provide the ad hoc module 210 with a list of ranking of anonymized users matched to one or more features specified by the advertiser 206.

The opportunity to display advertisements to users ranked above the list may be more valuable to the advertiser 206 than the opportunity to advertise to ranked users below the list. A ranked user at the top of the list may be more influential on the social network and may better fit the features specified by the advertiser 206. The ranking list of users may include information about each user, such as an anonymized user identifier (preventing an advertiser from identifying a particular user on the social network), an impact score, and a relevance score. Users can be ranked on the list based on influence scores, relevance scores, or a combination of these. In general, the greater the user influence and relevance score, the greater the likelihood that the user will be displayed above the ranking list.

The impact score may be a metric of user influence on other users of the social network. The influence score may be based on a user's activity level and / or an acquaintance relationship. A user's activity level may be a measure of a user's interaction on a social network.

An acquaintance relationship can be a connection relationship (e.g., a friend relationship) between two users on a social network. The user's influence score can be influenced by the amount and / or importance of the user's personal relationships.

For example, the level of activity of a user may be determined by the quality and / or quantity of the interaction between the user and other users in the social network; Can be determined by the quality and / or amount of the user-generated content in the social network; And / or the frequency of user interaction and / or content generation over time in the social network. A user with a good and / or good quality of interacted and / or generated content can be determined to have a higher activity level than a user with a lower quality and / or amount of content interacted and / or generated. In addition, a user with a high frequency of content and / or interaction generated within a time period may be determined to have a higher activity level.

In social networks, user interaction involves, at least, posting comments on other users' pages, sending messages to other users, participating in forums on social networks, adding other users as friends, chatting on social networks posting a comment in a chat room, and / or viewing another user's profile page. The content generated by the user may include at least uploading an image or video, updating a user profile page, posting an entry to a blog, and / or updating user status information.

The quality of interaction for a user in a social network can be determined by assessing the substantiveness of the interaction and / or the responsiveness of the interaction under the context in which the interaction occurs. For example, two comments about sports can be posted as follows: 1) "I like sports" and 2) "I like watching sports, especially football and hockey - at my Super Bowl party, Check out the photos posted on my profile. "The latter can be determined to be of better quality because the latter is more realistic.

In addition to the previous example, if two comments were to appear in response to a discussion of a musical genre, they are not likely to have a high level of quality, which would be interpreted in the context (eg, musical genre) This is because it is not a response. The reality is not high, but the comments that respond to the context in which you appear can be determined to have a higher quality than a real but off-topic comment. For example, a comment referred to in the discussion of the music genre as "the blues is my favorite type of music" can be determined to have a better quality than the above-mentioned very realistic second comment.

As with the quality of user interaction, the quality of user-generated content may also be assessed for the reality and responsiveness to the context. In addition, the quality of user generated content can be evaluated based on originality. User generated content that is unique (e.g., not already posted on a social network by another user) is determined to have a higher level of quality than the content that is not original (e.g., copied from another user's profile page) .

The amount of user interaction and user generated content in a social network can be determined by the number of interactions and the amount of content posted to the social network. For example, a user posting five comments can be determined to have a larger amount of activity than a user who posted two comments.

In some instances, the level of activity of a user may be determined by a combination of quality and quantity of user interaction and user generated content. The activity level may be determined by the weighted amount of user interaction and / or the weighted amount of content generated by the user, and each interaction and / or user generated content is weighted according to its quality. For example, a user who posted two comments similar to the second comment may have a higher activity level than a user who posted five comments similar to the first comment.

In addition, the level of activity of the user may be based, at least in part, on the frequency of the content and / or interaction generated by the user within the time period. For example, a user who interacts with five other users in the last month and posts ten new photos (e.g., content creation) may interact with only two other users last month, It can be determined to have a higher activity level than other users who have posted. The interacted and / or generated content may be additionally weighted according to the determined quality.

The influence score of the user can be influenced by the amount of the user's acquaintance relationship. Users with more friends may be more influential than users with fewer friends. As such, a user with a larger number of acquaintances may have a greater impact score than a user with fewer acquaintances.

The user's influence score can be influenced by the importance of the user's personal relationships. Users with more important personal relationships can have greater influence in social networks than users with less important personal relationships. The importance of the user's personal relationship may be based on the influence score of the user friend (the user connected to the user by the personal relationship) and / or whether the personal relationship links the individual sub-graphs of the social network.

In some instances, an acquaintance relationship with a user with a high impact score may be more important than an acquaintance relationship with a user with a low impact score. In another example, an acquaintance relationship with a user with a small influence score may be more important than an acquaintance relationship with a user with a high influence score.

The user's social network may be represented as a graph of users (nodes) connected to each other by an acquaintance relationship (edges), as exemplified by the friend relationship graph 218. [ An acquaintance relationship can be an explicit relationship between users of a social network. For example, a friend assignment between two users may be explicit. Also, an acquaintance relationship may be implicit. For example, even though the users U3 and U4 do not have an explicit friendship, the user U3 visits the user U4 profile page, the user U3 interacts with the user U4 via the interface on the social network (e.g., Exchange, etc.), and / or if user U3 and user U4 share a common friend (e.g., both have an explicit friendship with user U5), an acquaintance relationship may implicitly exist between them.

Within a social network graph, a sub-graph is a group of users who have many acquaintances with each other in a group, but have little or no relationship with users outside the group. An acquaintance linking users of two separate sub-graphs may be more important than an acquaintance linking users in the same sub-graph. For example, users U2, U4, U6, and U17 in the social network 118 are connected through the acquaintance relationships within the same sub-graph. The connection between the user U10 and the user U4 belonging to the sub-graph that is separate from the sub-graph to which U4 belongs can be considered to connect the users of the individual sub-graphs.

The relevance score may be a unit of similarity between a user's characteristics and the user characteristics requested by the advertiser 206 as a target of the ad. As described above in connection with the advertiser 206 request, user characteristics may include demographic information such as age or age range, gender, interest, occupation, income, educational background or geographic location of the user. A user with features similar to those requested by advertiser 206 has a greater relevance score than a user with less similar features. For example, suppose user U3 is "male, 25 years old, likes hockey" and user U5 is "male, 37 years old, likes blues music". For an advertiser who requests to display ads to "male" users of "ages 18 to 35" who like "sports", user U3 will have a greater relevance score for that request than user U5.

In some instances, the user activity level score may be determined in view of the relevance of each interaction to the advertiser's 206 request. In such an example, each interaction may be weighted according to the relevance to the features requested by the advertiser 206. For example, using the scenario in the previous paragraph, if users U3 and U5 posted the same number of realistic comments on the social network, but most of the posts of user U5 were about sports, user U5 would be more weighted You will have an activity level score.

In some implementations, the web server 214 may receive a ranking list of users by querying the database 216 hosted on the server side 204. The database 216 may include anonymized information associated with users of the social network. For example, the anonymized information may include information related to a user's characteristics, interactions in a social network, influence in a social network, and / or relevance to an advertiser 206 request.

In some instances, the database 216 may be populated with models associated with users of the social network. Models may provide synopsis of user features (including concerns) in a format that is maintained and queried. The models may generate information for insertion into the database 216 by the web server 214 or other server side 204 components not shown. For example, latent topic modeling can be used to generate models. Potential topic modeling may produce models by processing data from a social network (e.g., user profile pages, user interaction) to obtain user characteristics (e.g., interests).

Upon receiving the ranking list of users from the web server 214, the ad hoc module 210 may provide the advertiser 206 with a list of ranking of users. Advertiser 206 may then provide a bid to ad hoc module 210 for an opportunity to display an advertisement to one or more users included in the users' ranking list. The bid may specify a minimum bid per user, a maximum bid per user, and / or a total budget for propagating the advertisement via a social network. The advertiser 206 may bid for individual users and / or blocks of users in the ranking list.

The opportunity to display the advertisement to the higher ranking users in the ranking list may be more expensive than the opportunity to display the advertisement to the lower ranking users. It may be more expensive if the ranked user at the top of the list is more influential on the social network and more relevant to the features submitted by the advertiser 206 in relation to the advertisement. An advertiser 206 who desires to win an opportunity to display an advertisement to a user ranked above the list is likely to offer a higher bid for that user to a lower ranking user, Because they are likely to bid on the same influential same user.

In some implementations, the ad hoc module 210 may perform all or a portion of the functions performed by the web server 214 with respect to the ranked users of the social network. For example, in response to receiving an ad request from an advertiser 206, the ad hoc module 210 may send a request for a user list to the web server 214 without sending information about the ad content of the advertiser 206 . In response, the web server 214 may provide the ad hits module 210 with a list of users and their associated information (e.g., user impact scores, user interests). The ad hoc module 210 may then calculate a ranking for users based on the score of the received user's influence and / or similarity between the interests of the user and the content of the advertisement. After computing the ranking list, the ad hoc module 210 may display the ranking list to the advertiser 206 and receive user bids from the advertiser 206.

In some implementations, the ad hoc module 210 may request users to be placed within a predetermined impact score range or impact score percentage from the web server 214. For example, ad hoc module 210 may request web server 214 to return users with an impact score greater than 450. In another example, the ad hoc module 210 may request that the web server 214 return users with an impact score in the top 10% of the impact score. As described above, the ad hoc module 210 may then rank these users.

Adhit module 210 may submit a bid from advertiser 206 to web server 214. Web server 214 may receive bids for opportunities to display advertisements to users of the social network from a plurality of advertisers 206 via a plurality of ad hoc modules 210 104a-c < / RTI > The web server 214 may auction an opportunity to display advertisements to users of the social network based on the bids received from the advertisers 206. [ An auction can give advertisers who offer the highest bid a chance to display ads to users on the social network.

For example, Advertiser A1 may submit a maximum bid of $ 1.5 for an opportunity to display sports related advertisements to an anonymous user U1. Advertiser A2 may submit a maximum bid of $ 1.0 for the same opportunity to display the advertisement to user U1, while the advertisement of advertiser A2 relates to music. The auction conducted by the web server 214 will give the user U1 the opportunity to display the advertisement to the advertiser A1 with the larger maximum bid.

The web server 214 may propagate the advertisement to the gadget 212 associated with the user 208 after the auction has given the user the opportunity to display the advertisement. In some examples, gadget 212 is an interface that displays advertisements on a page that users can view on a social network. An advertisement of the winning advertiser 206 may be sent to the gadget 212 (the gadget 212 may display the advertisement to the user 208 via a computer display). Gadget 212 may provide the user with an interface that allows the user to interact with the advertisement. Gadget 212 may be a simple HTML or JavaScript application that may be embedded in a web page or other application. In some instances, the user interaction with the advertisement may include the user's own choice as to whether to propagate the advertisement to other users who are associated with him / her by the acquaintance relationship.

In some instances, a user interacting with the ad may share the revenue of the ad. In some instances, the revenue shared with the user is part of the revenue attributable to the user's interaction; Fixed amount; A quantity based on the number of users viewing and / or interacting with the advertisement due to user interaction; And / or influences of the users viewing and / or interacting with the advertisement due to the interaction of the user. For example, a user who interacts with an advertisement and decides to propagate the advertisement to other users of the social network may receive a share of revenue for that advertisement based on the number of users who have propagated the advertisement.

In some implementations, the propagation of an advertisement is attributed to the user only when the user has propagated the advertisement directly through one of the acquaintances. In another implementation, the propagation of an advertisement is attributable to the user only when it is possible to trace back the user's interaction in the chain of propagation of the advertisement from the user to the user. In such an implementation, the revenues attributable to the propagating user may be reduced as the user's propagation further detaches. For example, user U1 may receive 10% of the revenue from propagating the advertisement to user U2. However, when user U2 propagates the advertisement to user U3, user U1 may receive only 5% of the revenue. Similarly, when user U3 propagates the advertisement to user U4, user U1 may only receive 2.5% of revenue.

Gadget 212 may propagate the advertisement to other users of the social network based on the heat spreading model. Heat diffusion is a concept that comes from thermodynamics. In general terms, the heat spread specifies that the heat spreads (diffuses) from one adjacent particle to another when the heat (heat) between the two particles is different. For example, if particles A and B are adjacent, and they have temperatures of 70 degrees and 50 degrees, respectively, the heat will migrate from particle A to particle B. However, the heat will not migrate from Particle B to Particle A. If both particles A and B have a temperature of 70 degrees, heat transfer will not occur.

Using a heat spreading model, ads are propagated through a social network by assigning "temperature" to each user. If the ad has a higher " temperature " than the receiving user, the ad is delivered from the propagating user to the receiving user. In some implementations, the heat spread model uses the heat index score to indicate the user's temperature. The user's hit index score may be based on the user's influence score (described above) in the social network. A user's hit index score and influence score may have a direct relationship (e.g., a user with a larger influence score would have a larger hit index score).

Under a heat spread model structure, advertisements can propagate between " adjacent " users. The two users may be considered as adjacent if they are connected to each other in the social network, as indicated by the connection between the nodes on the friend relationship graph 218. [ The connection between users can take the form of an acquaintance relationship. An acquaintance relationship may in particular be a relationship in which users refer to friends, colleagues, classmates and / or members of the same group. In other implementations, an acquaintance relationship may indicate that the user has seen profiles with each other, posts content on a profile page for the user, and / or has received an electronic communication (e.g., a chat request from another user) have.

In some implementations, an advertisement is propagated from a propagating user to all users who are associated with the propagating user and have a lower hit index score than the propagating user. For example, user U3 is a propagating user with a hit index score of 70. User U3 is connected to users U5, U8, and U9 with hit index scores of 50, 35, and 80, respectively. The advertisements displayed to the propagating user U3 will spread to users U5 and U8 because they have lower hit index scores. Since user U9 has a higher hit index score than propagating user U3, the advertisement will not propagate to user U9. However, when an advertisement is displayed to user U9 and U9 acts as a propagating user, the advertisement displayed to user U9 will propagate to user U3 because user U3 has a lower hit index score.

Under the heat spreading model, advertising is propagated to users of the social network using circulation. The advertisement spreads from the propagating user to the receiving users, each receiving user being connected to the propagating user and having a lower hit index score than the propagating user. After the advertisement is displayed, each receiving user may act as a propagating user. As such, an advertisement is sent from a receiving user to other users who are connected to the receiving user and also have a lower hit index score.

For example, using the above scenario, assume that the user U9 has started as a user to propagate. The advertisement is displayed to the user U9, then has a lower hit index score and is propagated to users connected to him. In this case, the advertisement is propagated to user U3 because user U3 has a lower hit index score than user U9. User U3 acts as a user who subsequently propagates. By U3 as a propagating user, the advertisement propagates to users U5 and U8 because users U5 and U8 have lower hit index scores than user U3. Thereafter, users U5 and U8 will act as users to propagate. The ad will be sent to users U5 and also to users with a hit index score lower than U5. The ad will also be delivered to users who are connected to user U8 and who also have a hit index score lower than U8.

The cyclic propagation of the advertisement can continue until the termination condition is satisfied. In some instances, the termination condition may be when the advertising budget is exhausted. In another example, the termination condition may be that the propagating user chooses not to interact with the advertisement. In such an example, the gadget 212 may replace the advertisement with a replacement advertisement for display to the user 208. In another example, the termination condition may be a hit index score of the receiving user that is greater than the propagating user's hit index score. In another example, the termination condition may be the receiving user who has already received the ad.

The gadget 212 may send data to the web server 214 about the user 208 interacting with the advertisement. The transmitted data may include information about the viewing and clicking of the advertisement.

The web server 214 may comprise one or more servers. Web server 214 may include an interface 220, a request scoring module 222, an advertisement assignment module 224, and a circular propagation module 226. The interface 220 may communicate with the client side 202. The request scoring module 222 may score the bids received from the advertiser 206 for an opportunity to display an advertisement to at least one user of the social network. The advertisement assignment module 224 may assign an opportunity to display an advertisement to a user of the social network based on the bids scored by the request scoring module 222. [ The cyclic propagation module 226 may cyclically propagate the advertisement to users of the social network based on user impact scores.

3 is a flow chart of an exemplary process 300 that provides an opportunity to display advertisements to users of a social network based on an advertiser request. Processes 300 may be performed, for example, by a system such as systems 100 and 200, and for clarity of presentation, the following description uses systems 100 and 200 as an example to describe processes . However, other systems or combinations of systems may be used to perform the process 300.

Process 300 may begin at step 302 by receiving an advertiser's request to target users of the social network with the specified characteristics. The advertiser's request can be received from the client side on the server side. For example, the web server 214 may receive a request from the advertiser 206 at the client side 202.

In step 304, the process 300 may rank the users of the social network based on the similarity of the user characteristics to the specified characteristics and the user influence score. Ranking of users may be performed in response to a request received from an advertiser. For example, the web server 214 may classify users based on the profiled information and the information submitted by the advertiser 206 (this information specifies the characteristics of the users that the advertiser wants to target). In some implementations, the web server 214 may presort or rank users based on influence. For example, a user's influence ranking may be updated on a periodic basis (e.g., every hour). Next, when the users are ranked according to the features submitted by the advertiser, the pre-calculated rankings of the influences can be combined with the feature rankings to generate user rankings based on user influence and characteristics.

In some embodiments, the process 300 may also include sending a ranking list of users to the advertiser making the request. Some embodiments may also include receiving advertiser bids for opportunities to display advertisements to users on the ranking list. The advertiser bids may include bids for opportunities to display advertisements to individual users and / or bids for opportunities to display advertisements in groups of users. For example, an advertiser may bid $ 1.00 for an opportunity to display an advertisement to user U3, and $ 2.50 for an opportunity to display an advertisement to users U4-U8.

In some implementations, the group of users may be a range of ranked users. For example, an advertiser may bid on the opportunity to display advertisements to users ranked in the top-10 on the ranking list. In some implementations, the bid amount for a group of users may correspond to the amount of all users in the group (e.g., $ 1.00 for all users U4-U8). In another implementation, the bid amount for a group of users may correspond to an amount for each user in the group (e.g., one dollar for each of the users U4-U8).

The process 300 may score advertiser bids for the opportunity to display advertisements to users of the social network at step 306. [ For example, the scoring may be based on the amount the advertiser has bid on the opportunity to display the advertisement to a user of the social network. There may be a direct relationship between the resulting score and the bid amount (e.g., the larger the bid amount, the larger the resulting score).

The bids can also be scored based on how relevant users in the past have found the advertisers' advertisements. For example, the database on the server-side 204 may store information indicative of a historical click-through rate for advertisements submitted by particular advertisers. Bids from advertisers with high click-through rates may be scored higher than those from advertisers with low click-through rate advertisements.

In some implementations, a score may be provided for an advertiser's bid for an opportunity to display advertisements in a group of users. In some implementations, an advertiser bid for an opportunity to display an advertisement in a group of users may be provided with a score for each of the individual users of the group. In some embodiments, the score for an individual user in the group may be the same as the scores for other users in the group (e.g., score for individual users = score for user groups / number of users). In another embodiment, the score for an individual user of the group may be a share of the score for the group, which is proportional to the user's influence score on the influence score for the other users (e.g., individual user score = Score × (individual user's influence score / group's total influence score).

In step 308, an advertisement opportunity may be assigned to the advertiser. Assigning advertising opportunities may be based on scores of advertiser bids and / or scores associated with users whose ads are to be displayed. Advertisers may be assigned advertising opportunities for individual users and / or group users. The bids considered when assigning an advertising opportunity may be limited to bids received within a certain time span and / or bids for displaying advertisements to a user within a certain date range.

In some implementations in which an advertiser submits a group bid and a group bid is scored for each user in the group, the opportunity to display an advertisement in the group is determined for each user in the group by the advertiser If it is greater than the bid scores, it can be assigned to the advertiser. For example, if an advertiser bids to display advertisements to users U4-U8 and the bids are individually scored (e.g., 1.0 for each user) for each user, some of the users U4-U8 If there is no advertiser with a bid score that is greater than 1.0 (or smaller depending on the scoring technique) for the advertiser, then the opportunity to display the ad to the group may be granted to that advertiser.

In some other implementations where an advertiser submits a group bid and a group bid is scored for each user in the group, the opportunity to display an advertisement to each user in the group may be evaluated and assigned for each user separately. For example, if an advertiser bids to display an ad on U4-U8 and the bid is individually scored (e.g., 1.0 for each user) for each user, a bid greater than 1.0 for user U4 If there is no advertiser with a score, the opportunity to display the advertisement to user U4 may be assigned to that advertiser. The opportunity to display advertisements to users U5-U8 can be assigned in a similar manner, independent of evaluating and assigning opportunities to other users in the group.

For some implementations in which an advertiser submits a group bid and a group score is provided to the group bid, the opportunity to display in the group may be assigned to the advertiser who made the highest ranked bid for that group. For example, if the first and second advertisers have auction scores of 2.5 and 2.7 for the opportunity to display advertisements to users U4-U8, then the second advertiser has the opportunity to display advertisements to users U4-U8 Can be assigned.

In some implementations where an advertiser submits a group bid and a group score is provided to the group bid, the minimum score required to display the advertisement to each individual user is determined, the minimum score for the group is aggregated, Is less than or equal to the group bid score, this advertisement opportunity can be assigned by assigning an opportunity to the advertiser. For example, if the advertiser's bid score for a group of users U4-U8 is 2.5 and the aggregate minimum score for displaying an ad in the group is 2.4 (e.g., minimum for displaying advertisements to each of users U4-U8) 0.0 > 0.2, < / RTI > 0.2 and 0.2, respectively), advertisers may be assigned the opportunity to display the group. The minimum score required to display an advertisement to a user may be determined by ascertaining the highest bid score for the user and increasing the highest bid score by a predetermined amount and / or percentage.

In some implementations, there may be more than one opportunity to display an advertisement to a user within a time period. These opportunities can be assigned to the same or different advertisers depending on the bid scores. For example, if there are three opportunities to display an advertisement to a user within a time period, the three highest bid numbers may be assigned to the three opportunities. For example, if four advertisers A1-A4 bid on an opportunity to display an advertisement to four users U1-U4 and there are three opportunities available per user, Advertisers who bid will be given the opportunity to display their ads. A1 bids $ 2 for users U1-U4, A2 bids $ 1.50 for users U1-U3, A3 bids $ 1 for users U2-U4, and A4 bids users U1-U3 If you bid $ 0.5 for U4, an advertising opportunity can be assigned to each user as follows: U1- A1, A2, A4; U2 - A1, A2, A3; U3 - A1, A2, A3; U4 - A1, A3, A4; U5-No chance assigned.

In some implementations, when there are multiple opportunities to display advertisements to a user, if a single advertiser has bid on more than one of a plurality of opportunities, the single advertiser may be assigned two or more of the multiple opportunities.

After assigning an advertisement opportunity for a user or users to an advertiser, the advertiser's ad may be output to a user or users, at block 310. The user or users who received the advertisement may be on the client side, such as users 118 or users 208 specified in the social network.

In some implementations, users of the social network where the advertisement opportunity is not assigned, such as user U5 in the previous example, may receive default advertisements instead of advertisements assigned to the advertiser (e.g., , Profiles of other users on the social network, advertisements for non-profit / charitable organizations, etc.).

4 is a flow chart of each exemplary process 400 for cyclically propagating advertisements through users of a social network. For example, the processes 400 may be performed by a system such as the systems 100 and 200, and the following description uses the systems 100 and 200 as an example, for the sake of clarity of presentation. However, the combination of other systems, systems, can be used to perform the process 400.

Process 400 may begin at steps 402 and / or 404. At step 402, the process 400 may determine an acquaintance relationship (e.g., a friend relationship) between users of the social network. At step 404, the process 400 may determine activity levels (e.g., number of posts, friend additions, etc.) for users of the social network.

At step 406, the process 400 may use the determined user relationship and determined user activity levels to generate an impact score for users of the social network. Combining the user ' s personality and activity levels to generate impact scores may be implemented differently depending on the composition of the social network and / or advertiser preferences. For example, the first social network may be configured to weight relationships that are twice as high as the activity level, while the second social network may be configured to equally weight the acquaintance and activity levels.

In some implementations, the social network may have a number of configurations used to generate impact scores for users of the social network. The determination of the social network for the configuration to use among the plurality of configurations may depend on the conditions within the social network and / or the type of advertisement to be displayed. For example, the configuration used by the social network during the week may be different from the configuration used during the weekend. Other configurations may be determined by the social network based on demographic information of users accessing the social network for various time periods.

In some implementations, a social network may follow an advertiser's weight on an acquaintance and activity level when generating impact scores for users of the social network. The use of influence scores generated according to the advertiser's weight may be limited to advertisements from that advertiser. The advertiser may provide the social networks with weights that apply to particular advertisements from that advertiser.

The generation of impact scores for users of the social network at step 406 may be performed periodically and / or when certain events occur. For example, impact scores may be generated every 10 minutes, 30 minutes, 1 hour, 6 hours, 12 hours, 1 day, 3 days, weeks and / or months. As another example, influence scores may be generated when a predetermined number of activity events occur within a social network (e.g., generate impact scores every time: 1000 comments are posted on the social network, 10 users are social Joining the network, forming 100 personal relationships, etc.).

In some implementations, the creation of impact scores for users of the social network at step 406 may be triggered by an advertisement display for a user of the social network. Each time an advertisement is first displayed to a user on a social network, the social network may generate an impact score for the users of the social network. When an advertisement triggers generation, the generation of an impact score may be restricted to users in the sub-graph of the initial target of the advertisement.

In some implementations, the process 400 may display an advertisement to a user of the social network. The opportunity to display an advertisement to a user can be granted to an advertiser who has won an opportunity through the bidding process, e.g., as described with reference to FIG.

In step 408, the process 400 may determine whether the impact score for the propagating user is greater than the influence score for the receiving user. The propagating user may be the user whose advertisement is displayed. The receiving user may be a user connected through an acquaintance relationship (e.g., a friend relationship) to the propagating user. If the impact score for the propagating user is greater than the influence score for the recipient user, then the process 400 propagates the advertisement to the receiving user from the propagating user,

In some instances, steps 402-406 for generating an impact score may not be performed until step 408. [ In such an example, steps 402-406 may be implemented only for the propagating user and the receiving user. For example, after an advertisement is displayed to a propagating user, the process 400 may determine influence scores for the propagating user and receiving users.

At step 410, propagating the advertisement from the propagating user to the receiving user may include displaying the advertisement to the receiving user. The advertisement displayed to the receiving user may be the same advertisement displayed to the propagating user. After propagating the advertisement to the receiving user in step 410, the process 400 may return to step 408. [ Returning to step 408, however, the receiving user acts as a propagating user, and the connected user to the receiving user may act as the receiving user.

For example, if user U1 is the first propagating user, user U2 is the first recipient user, and the impact score of U1 is greater than the impact score of U2, then the advertisement displayed in U1 may be propagated to U2. After the advertisement is propagated to U2, the process 400 may return to step 408, where U2 acts as a propagating user, and U3, which is connected through an affinity relationship to U2, acts as a receiving user.

In steps 408 and 410, advertisements may propagate cyclically between users of the social network. Steps 408 and 410 may be performed for each person's knowledge of the propagating user. For example, an advertisement displayed to a propagating user can be propagated to each of the propagating users and each of the acquaintances with a smaller impact score than the propagating user. Next, each user who receives an advertisement from a propagating user can propagate the advertisement to each user who has a smaller influence score and also in an acquaintance relationship.

The cyclical propagation of the advertisement in steps 408 and 410 may continue until the influence score of the user that the process 400 is propagating is determined to be not greater than the influential score of the receiving user. If such a determination is made, the process 400 may be terminated. Also, cyclic propagation may be terminated when conditions that do not allow continuous propagation of the ad (e.g., the conditions outlined in connection with FIG. 7) are met.

In some instances, propagation using a heat spreading model may be limited based on the degree of separation between users. For example, if an advertisement propagates from a first user to a user with a degree of separation greater than 6, the propagation can be stopped regardless of the hit index score of the adjacent users.

5 is a flow chart of an exemplary process 500 for generating a user's interest model from user generated content. For example, processes 500 may be implemented by systems such as systems 100 and 200, and for clarity of presentation, the following description uses systems 100 and 200 as an example to describe a process . However, a combination of different systems and systems may be used to implement process 500.

The process 500 may begin at step 502 by collecting information about the user based on the user-generated content. The collected information may include demographic information (e.g., age, gender, geographical location, etc.) and / or user interests (e.g., sports, music, etc.). The user generated content may include information (e.g., interest, age, gender, etc.) that the user has provided on his or her profile page, groups the user has joined (e.g., a group of hiking clubs), and / , Status updates, comments posted on other user's profile pages), and the like.

In some instances, visual and audio media (e.g., music, pictures, videos) posted by the user may also be collected. Meta-tags associated with visual and audio content can be collected. In some instances, the audio / visual content analyzer may be used to derive information related to visual and audio content. For example, an audio / visual analyzer can identify an audio file by comparing a calculated file signature for the audio file to a database of well-known audio files. In another example, the audio / visual analyzer may attempt to find information about the content of the photograph by looking for items and / or logos in the photograph that can be associated with a particular subject (e.g., baseball cap, baseball glove , And / or looking for a baseball team logo on an image may represent a picture of the baseball).

At step 504, the process 500 may enter the collected information into a machine learning algorithm. The machine learning algorithm may be a latent topic modeling algorithm. The potential topic modeling algorithm may examine the collected information based on the presented topics and generate a list of topics appropriate for the user. In some implementations, the algorithm may collate the collected information against a database of keywords associated with topics. The algorithm can dynamically learn and adjust these keywords and associated topics.

At step 506, the process 500 may generate a topic model that provides the user's interests based on the collected information. The topic model for the user may provide a list of attributes associated with the user ' s interests. The topic model may provide an indication of how much the user is interested in a particular topic (e.g., the user is most interested in sports and then interested in music). After the topic model is created, the process 500 may terminate.

In generating the topic model, the previous topic models may be examined to determine a change in the user's interest over time. For example, a topic model can provide that a user has recently become interested in genealogy, and that the user's interest in the sport has been reduced over the past year.

For example, the user U10 may have blog entries about soccer and skiing, and profile pages with recent professional soccer game photos the user attended. The user U10 may also be a member of a video game group on a social network, or may post comments on other users' profile pages regarding the snow status of football, movies and ski areas. The entirety of this information can be collected by the process 500 and entered into a machine learning algorithm. Using the machine learning algorithm, the process 500 may then generate a topic model for the user U10. Topic models can list the following concerns in order of highest interest to least interest: soccer, skiing, movies, and video games. By examining the previous topic models of the user U10, the topic model can provide that the football is consistently the greatest concern of the user U10, the ski is a periodic interest that is peak in winter, and the movie and video game has been reduced for the past year .

FIG. 6 is a flow chart of an exemplary process 600 in which an advertiser bids for an opportunity to display advertisements to users of the social network. Process 600 may be implemented by a system such as, for example, systems 100 and 200, and for clarity of presentation, the following description uses systems 100 and 200 as examples to illustrate processes. However, other systems or combinations of systems may also be used to implement the process 600.

The process 600 may begin at step 602 with the advertiser entering parameters describing the characteristics of the users that the advertiser desires to target the advertisement. Features may include demographic information (e.g., age, gender, geographic information) and / or interests (e.g., sports, music). The advertiser may enter this information through an interface on the client side, such as the ad hoc interface 210 of the system 200, and such information may be submitted to the server side, such as the web server 214 of the system 200 .

At step 604, the process 600 receives a list of ranked users from the server, and the ranking is based on similarity of features and user impact scores. The ranking list of users may be generated at a server, such as web server 214, in a manner similar to that described above with respect to Figures 1-3. The ranking list of users may be received via the same interface as the ad hoc interface 210 of the system 200.

For example, Advertiser A1 can enter parameters for users to be targeted for an advertisement, such as a man between 18 and 35 years of age who is interested in sports. Advertiser A1 can then receive a list of ranked users U1-U5. User U1 at the top of the list can be matched most closely to the features submitted by Advertiser A1 and can have a high impact score in the social network. The user U5 located at the bottom of the list may be the least likely to match the features submitted by Advertiser A1 and / or have a low impact score in the social network.

At step 606, the advertiser may enter the maximum and minimum costs that the advertiser can pay per user to display the ad. In some instances, an advertiser may enter the maximum and minimum costs that he or she may pay to display ads on a block or group of users. The maximum and minimum costs may be entered via an interface, such as the ad hoc interface 210 of the system 200.

Using the previous example, the maximum and minimum costs for users U1-U5 that advertiser A1 can pay are directly related to the ranking of each user in the list received in step 604. [ Advertiser A1 may enter the maximum and minimum costs for user U1 at $ 1 and $ 0.5, respectively. However, advertiser A1 may enter the maximum and minimum costs of $ 0.25 and $ 0.05 for user U5, respectively. In some instances, advertiser A1 may not enter bids for lower ranking users, such as user U5.

In step 608, the advertiser may enter a total budget for displaying the advertisement. The total budget may be the maximum amount that an advertiser can consume to allow ads to be displayed to users upon bidding and propagated to other users of the social network. If the budget is exhausted, the advertisement may stop being displayed to users of the social network. The total budget may be entered via an interface, such as the ad hoc interface 210 of the system 200.

In some instances, budgets may exist periodically or for a specific time period. For example, an advertiser may specify that a daily budget for displaying an ad is $ 50.00. If the daily budget is exhausted, the ad may not be displayed to users of the social network until the next day.

In step 610, the advertiser may submit bids (e.g., maximum and minimum costs) for an opportunity to display advertisements to users from the ranking list. In addition to bidding, an advertiser may also submit a total budget for the ad. The bidding may be submitted by an advertiser via an interface such as the ad hoc interface 210 of the system 200 and may be received by a component on the server side, such as the web server 214. After the advertiser submits the bid, process 600 may end.

The steps 606-610 may collectively display the bidding process 612 performed by the advertiser for the opportunity to display advertisements to users of the social network. The bidding process 612 may be performed periodically (e.g., monthly) by an advertiser for a particular ad. In some instances, the bidding process 612 may be automated for advertisers based on advertiser's previous bids for similar advertisements. For example, if the advertiser has provided average maximum and minimum bids for users in the first and fifth ranks of $ 1.00 - $ 0.50 and $ 0.25 - $ 0.05, respectively, then the bidding process 612 may, as part of the new bid, These average values may be automatically utilized for the first and fifth rank users.

In some instances, the automatic bid amount may be based, at least in part, on the user's influence scores and rankings in the user's ranking list. For example, the automatic bid amount may be based on a bid amount per user impact score (e.g., bid amount / user impact score / user ranking) on the user ranking. Since the user impact score and user rank can be provided to the advertiser in step 604, the bid amount can be automatically calculated for each user on the ranking list. In some examples, a threshold of the calculated bid amount (e.g., a bid amount greater than $ 0.01), a user influence score (e.g., a score greater than the average influence score), and / To be performed in order to perform automatic bidding.

7 is a flowchart of an exemplary process of propagating an advertisement from a propagating user to a receiving user. Process 700 may be implemented by a system such as, for example, systems 100 and 200, and for clarity of presentation, the following description uses systems 100 and 200 as examples to illustrate processes. However, other systems or combinations of systems may also be used to implement process 700.

The process 700 may begin at step 702 where a user of the social network logs in to the social network. In step 704, the user can view the advertisement in the gadget. The gadget may be an interface of interaction included in a view of the user of the social network, such as the gadget 212 described with reference to the system 200. For example, the gadget may be an interactive widget that is displayed in a user web page based view of the social network. The gadget may display an advertisement that the advertiser has won the opportunity to display to the user. The gadget may also display ads propagated to the user from other users on the social network.

In step 706, the process 700 may determine whether the user interacts with the advertisement being displayed on the gadget. The user interaction may include clicking an advertisement, providing an indication of interest in the advertisement (e.g., depressing a "play" button for a video advertisement), and / or advertising to other users of the social network If the user interacts with the advertisement displayed on the gadget, then the process 700 proceeds to step 708. If the user does not interact with the advertisement displayed on the gadget, The process 700 does not propagate the advertisement in step 718. [

In some implementations, step 706 determines whether the process 700 warrants that the user's interaction warrants propagation of the advertisement to other users of the social network (e.g., propagation to users associated with the user by an acquaintance) It can be judged. For example, in an ad propagation to occur, the user may indicate that they agree with the radio wave through a kind of interaction with the gadget (e.g., clicking on the "radio advertisement" button). If the user indicates agreement for the propagation, the process 700 may then proceed to step 708. [ Although the user may interact with the advertisement, if the user does not support propagation of the advertisement, the process 700 does not propagate the advertisement in step 718. [

In step 708, the process 700 determines whether the budget of the advertisement has been exhausted. As described with reference to process 600, an advertiser may provide a total budget for displaying advertisements. If the budget is exhausted by displaying advertisements to users of the social network, the advertisement can not be propagated. If the budget has not been exhausted, the process 700 proceeds to step 710. If the budget is exhausted, the process 700 does not propagate the advertisement in step 718.

In step 710, the process 700 determines whether the time period for displaying the advertisement has expired. The advertiser may specify that the advertisement is displayed within a certain time period. For example, with respect to an advertisement for a music concert, the advertiser may specify that the advertisement should be displayed until the concert time, rather than after the concert. If the time period for displaying the advertisement has not expired, the process 700 proceeds to step 712. When the time period for displaying the advertisement expires, the process 700 does not propagate the advertisement in step 718. [

In step 714, the process 700 determines whether the advertisement has already been propagated to all of the users associated with the user by an acquaintance relationship. As described above, an acquaintance relationship may include, for example, posting a comment on another user's profile page, viewing a profile page of another user, social network support activities (e.g., playing an online game together via a social network, And / or a connection between two users of the social network that belong to a similar social group or organization in a social network. If the advertisement has not been propagated to at least one of the users associated with the user by an acquaintance relationship, the process 700 proceeds to step 714. If the advertisement has already been propagated to all of the users associated with the user by an acquaintance relationship, the process 700 does not propagate the advertisement in step 718. [

In step 714, the process 700 determines whether the heat spread balance has occurred between the user and the users associated with the user (the ads have not yet propagated to them and are also connected by an acquaintance relationship). As described above with reference to step 408 of process 400, an advertisement may propagate from one user to another unless a heat spread balance is achieved. If the heat spread balance is not made by at least one user connected to the user by way of an acquaintance, then the process 700 proceeds to step 716. If the heat spread balance is made by all users connected to the user by an acquaintance relationship, the process 700 does not propagate the advertisement in step 718. [

At step 716, the process 700 propagates the advertisement to the receiving user (e.g., a user associated with the user who propagates it by way of an acquaintance) from the user (e.g., the propagating user). The receiving users may be users who are connected to the propagating user in an acquaintance relationship and have influence scores that are smaller than the propagating user's influence score, and the advertisement has not yet propagated. In some implementations, the advertisement may be propagated to all receiving users. In another implementation, the advertisement may only propagate to receiving users that meet the criteria set by the advertiser. For example, an advertiser can direct a propagation to a receiving user to occur only when the receiving user has an impact score greater than 80% of the propagating user's impact score. After propagating the advertisement for the receiving user, the process 700 may end.

At step 718, the process 700 does not propagate the advertisement to users connected to that user by an acquaintance relationship from the user. After step 718, the process 700 proceeds to step 720. [ In step 720, the process 700 determines whether there is an alternative advertisement that can be displayed to the user in the gadget. The alternate ad can be another advertisement that can be displayed to the user (e.g., an advertiser wins the opportunity to display the replacement ad to the user, and the ad propagates to the user). If the replacement advertisement can be displayed to the user, the process 700 can return to step 704 and display the replacement advertisement to the user in the gadget. If a replacement advertisement can not be used, the process 700 may terminate.

The system 800 includes a processor 810, a memory 820, a storage device 830, and an input / output device 840. Each of the components 810, 820, 830 and 840 is interconnected using a system bus 850. The processor 810 may process instructions for execution within the system 800. A processor may be designed using some of the multiple architectures. For example, the processor 810 may be a Complex InstructionSet Computers (CISC) processor, a Reduced Instruction Set Computer (RISC) processor, or a Minimal Instruction Set Computer (MISC) processor.

In one implementation, processor 810 is a single-threaded processor. In other implementations, the processor 810 is a multi-threaded processor. The processor 810 is capable of processing instructions stored in the memory 820 or on the storage device 830 to display graphical information for the user interface on the input / output device 840. [

The memory 820 stores information in the present system 800. In one implementation, the memory 820 is a computer-readable medium. In one implementation, memory 820 is a volatile memory unit. In other implementations, memory 820 is a non-volatile memory unit.

The storage device 830 may provide a large amount of storage for the system 800. [ In one implementation, the storage device 830 is a computer-readable medium. For various other implementations, the storage device 830 may be a floppy disk device, a hard disk device, an optical disk device, or a tape device.

The input / output device 840 provides input / output operations for the present system 800. In one implementation, input / output device 840 includes a keyboard and / or pointing device. In other implementations, the input / output device 840 includes a display unit for displaying a graphical user interface (GUI).

The above-described features may be implemented in digital electronic circuitry, computer hardware, firmware, software, or a combination of any of the foregoing. The device may be implemented as an information transmitter, i.e., a machine-readable storage device or a computer program product tangibly embodied for execution by a programmable processor in a propagated signal; The method steps may be performed by a programmable processor that executes a program of instructions for performing the functions of the implementations described above by acting as input data and generating an output. The above-described features may be implemented in a programmable system including at least one programmable processor, at least one input device, and at least one output device coupled to receive data and instructions from a data storage system and to transmit data and instructions And may be advantageously implemented in one or more computer programs executable. A computer program is a set of instructions that can be used directly or indirectly by a computer to perform any action or to obtain an arbitrary result. A computer program may be written as a form of programming language including compiled or interpreted languages and may be in the form of a stand-alone program or module, component, subroutine, or other unit suitable for use in a computing environment Lt; / RTI >

Suitable processors for execution of the instruction program may include, by way of example, both general purpose and special purpose microprocessors, and either single processor or one of multiple processors of a type of computer. Generally, a processor will receive commands and data from either read-only memory or random access memory, or both. An essential factor of the computer is a processor for executing instructions and one or more memories for storing instructions and data. In general, the computer will also include one or more mass storage devices for storing data files, or may be operatively coupled to communicate with the mass storage devices. Such devices include magnetic disks such as internal hard disks and removable disks; Magneto-optical disks; And an optical disk. Storage devices suitable for implementing computer program instructions and data types include, by way of example, EPROM, EEPROM, flash memory devices; Magnetic disks such as internal hard disks and removable disks; Magneto-optical disks; And non-volatile memory, including semiconductor memory devices such as CD-ROM and DVD-ROM disks. The processor and the memory may be supplemented or integrated by application-specific integrated circuits (ASICs).

To provide for interaction with a user, the feature may include a display device, such as a cathode ray tube (CRT) or liquid crystal display (LCD) monitor, for displaying information to a user, Such as a keyboard and mouse or a pointing device such as a trackball.

The features may include a back-end component such as a data server, a middleware component such as an application server or an Internet server, a front-end component such as a client computer with a graphical user interface or an Internet browser front-end component) or a combination of the above. The components of the system may be connected by any form or medium of digital data communication, such as a communications network. Examples of the communication network include a LAN (Local Area Network), a WAN (Wide Area Network), a computer for establishing the Internet, and a network.

The computer system may include a client and a server. Clients and servers are usually separate from each other, and generally interact through the network as described. The relationship between a client and a server is generated by a computer program running on each computer and having a client-server relationship to each other.

While some implementations have been described in detail above, other variations are possible. Other mechanisms for providing advertisements to users of social networks may also be used. In addition, the logic flow shown in the drawings does not necessarily require the specific order shown, or a sequential order, to obtain the desired result. Other steps may be provided, or steps may be removed from the described flow, and other components may be added to or removed from the described systems. Accordingly, other implementations are within the scope of the following claims.

Claims (26)

A computer-implemented method,
Receiving, at a server, information indicating activity levels of computer-implemented social network users or of the users on the computer-implemented social network;
Generating, by the server, influence scores for the users based on the received information;
When the difference between the first influence score of a propagating user and the second influence score of a recipient user is greater than a threshold, an advertisement is sent from the propagating user to the recipient user Propagating the advertisement cyclically by the server through the computer-implemented social network among users having an acquaintance relationship; And
Terminating, by the server, the cyclic propagation of the advertisement over the social network when each of the receiving users having an affinity relationship with a particular propagating user has an impact score that is greater than or equal to the influencing score of the propagating user Methods of inclusion. The method according to claim 1,
And after the advertisement is sent to the recipient user, the recipient user acts as a second propagating user. The method according to claim 1,
Wherein terminating the cyclic propagation of the advertisement by the server comprises: when the impact score of a particular propagating user is less than or equal to the influence score of a particular recipient user, the cyclical propagation of the advertisement via the computer implemented social network Lt; RTI ID = 0.0 > by the server. ≪ / RTI > The method according to claim 1,
Wherein the step of terminating the cyclic propagation of the advertisement by the server comprises: when the server receives an indication that a particular propagating user has rejected the opportunity to propagate the advertisement via the computer-implemented social network, Further comprising terminating the cyclic propagation of the advertisement via the network by the server. The method of claim 4,
Wherein the indication is generated by a client associated with the particular propagating user in response to the action of the particular propagating user representing indifference to the advertisement. The method of claim 4,
Replacing the advertisement with an alternate advertisement by the server after the user has rejected the interaction; and, by the server, to cause the alternate advertisement to be circulated through the social network among users with an acquaintance relationship ≪ / RTI > The method according to claim 1,
Wherein terminating the cyclic propagation of the advertisement by the server further comprises terminating the cyclic propagation of the advertisement via the social network by the server when the time period for the advertisement expires. delete The method according to claim 1,
Wherein the step of terminating the cyclic propagation of the advertisement by the server comprises the step of, when each receiving user having an acquaintance relationship with a particular propagating user has already received the transmission of the advertisement, ≪ / RTI > further comprising terminating the cyclic propagation of the signal. The method according to claim 1,
Wherein terminating the cyclic propagation of the advertisement by the server further comprises terminating the cyclic propagation of the advertisement via the social network by the server when the target number of propagations for the advertisement is met How to. The method according to claim 1,
Wherein terminating the cyclic propagation of the advertisement by the server further comprises terminating the cyclic propagation of the advertisement via the social network by the server when the budget for the advertisement is exhausted. The method according to claim 1,
Further comprising, by the server, providing the propagating user with an opportunity to interact with the advertisement. The method of claim 12,
Further comprising providing compensation to the propagating user by the server when the propagating user chooses to propagate the advertisement by interacting with the advertisement. 14. The method of claim 13,
Further comprising calculating an amount of compensation by the server based on the number of receiving users for which the advertisement has been propagated. The method of claim 12,
Wherein in a gadget disposed on a display of the propagating user of the computer-implemented social network, the opportunity to interact is provided to the propagating user. The method of claim 12,
Wherein the propagating user interacts with the advertisement by adding comments about the advertisement or by clearly specifying one or more users to receive the advertisement based on interaction with the advertisement. The method according to claim 1,
Further comprising the step of obtaining, by the server from the propagating user and each receiving user, data regarding propagation of the advertisement via the computer-implemented social network. 18. The method of claim 17,
Wherein the propagation data includes information regarding a number of users who viewed the advertisement, a number of users who interacted with the advertisement, or a number of users who have propagated the advertisement. The method according to claim 1,
The step of cyclically propagating the advertisement through the computer-implemented social network comprises applying a heat diffusion model to the first influence score and the second influence score to determine the threshold value Wherein the heat spreading model is associated with a path through which the advertisement can propagate through a computer-implemented social network. As a system for propagating advertisements to users of social networks,
One or more servers;
An interface to the one or more servers for receiving information indicative of an activity level of users of the social network or an acquaintance relationship of the users on the social network;
Means for generating influence scores for the user based on the received information; And
When a difference between a first influence score of a propagating user and a second influence score of a receiving user is greater than a threshold value, an advertisement is sent from the propagating user to a receiving user, To propagate the ad cyclically, and
Wherein when each of the receiving users having an acquaintance relationship with a particular propagating user has an impact score that is greater than or equal to the impact score of the propagating user, the cyclical propagation of the advertisement via the social network is terminated by the server Wherein the server comprises a cyclic propagation module. The method of claim 20,
Wherein the cyclic propagation module allows the receiving user to act as a second propagating user after the advertisement is sent to the receiving user. delete A computer-implemented method,
Outputting an advertisement to a first user of a computer-implemented social network, the output causing the advertisement to be displayed to the first user;
Receiving an input associated with the advertisement from the first user;
Retrieving influence scores for the first user and influencing scores for second users of the social network associated with the first user by an acquaintance relationship;
Cyclically propagating the advertisement to the second users having an impact score less than the impact score for the first user; And
And terminating the propagation of the advertisement by the server when the second user having an affinity relationship with the first user has an influence score that is greater than or equal to the influence score of the first user. 24. The method of claim 23,
Generating influence scores for the second users of the computer-implemented social network, the influence scores for the first user, and the influence scores associated with the first user by an acquaintance relationship. 27. The method of claim 24,
The step of generating an influence score for a user may include the step of determining whether the user has an influence on the user based on the user's personal relationship and the activity level of the user on the computer- And calculating an amount of the influence having an influence. 24. The method of claim 23,
Wherein the input from the first user includes an indication that the first user desires the advertisement to propagate to the second users of the social network.

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