Bidding on Users

• US 20100228631A1
• Filed: 03/02/2010
• Published: 09/09/2010
• Est. Priority Date: 03/03/2009
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Chang, Edward Y., Zhang, Dong
• Granted Patent: US 9,996,845 B2
• Time in Patent Office: Days
• US Class Current: 705/14.660
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: G06Q 30/0277 Online advertisement

Abstract

In one implementation, a computer-implemented method includes receiving at a server a request from an advertiser to target an ad to users of a computer-implemented social network, the request comprising data representing characteristics of the users that the advertiser desires to target. The method further includes ranking the users based on how similar the users'"'"' characteristics are to the received characteristics and an influence score for each user that indicates how influential the user is within the social network. The method also includes scoring the advertiser'"'"'s request based on a bid from the advertiser for an opportunity to display the ad to one or more of the users and assigning the opportunity to display the ad to the one or more users based on a correlation between a score of the advertiser'"'"'s request and one or more rankings of the one or more users.

Claims

1. A computer-implemented method comprising:

receiving at a server a request from an advertiser to target an ad to users of a computer-implemented social network, the request comprising data representing characteristics of the users that the advertiser desires to target;

ranking by the server the users based on how similar the users'"'"' characteristics are to the received characteristics and an influence score for each user that indicates how influential the user is within the computer-implemented social network;

scoring by the server the advertiser'"'"'s request based on a bid from the advertiser for an opportunity to display the ad to one or more of the users targeted by the advertiser;

assigning by the server the opportunity to display the ad to the one or more users targeted by the advertiser based on a correlation between a score of the advertiser'"'"'s request and one or more rankings of the one or more users; and

outputting by the server the ad for display on one or more clients associated with the one or more users assigned to the ad.

2. The method of claim 1, further comprising generating by the server the influence score for a user based on the user'"'"'s level of activity on the computer-implemented social network.

3. The method of claim 2, further comprising determining by the server the level of activity of the user based on a quality or type of content generated by the user on the computer-implemented social network;

a quality or type of interactions with other users on the computer-implemented social network;

or frequency of user interaction within the computer-implemented social network over a period of time.

4. The method of claim 2, further comprising determining by the server the level of activity of the user based on an quality of content generated by the user on the computer-implemented social network or a quality of interactions with other users on the computer-implemented social network.

5. The method of claim 3, wherein the influence score for a user indicates greater influence when the content generated by the user or the interactions with other users are determined to be substantive, wherein substantive content comprises original content that is greater than a threshold amount of content.

6. The method of claim 1, further comprising generating by the server the influence score for a user based on the user'"'"'s acquaintance relationships on the computer-implemented social network, wherein an acquaintance relationship comprises a bi-directional relation between two users of the social network.

7. The method of claim 6, wherein an acquaintance relationship comprises a link between two users of the computer-implemented social network.

8. The method of claim 6, wherein a user with a greater number of acquaintance relationships has an influence score indicating greater influence than a user with a smaller number of acquaintance relationships.

9. The method of claim 6, wherein the user'"'"'s influence score is based on influence scores of other users who have acquaintance relationships with the user.

10. The method of claim 6, wherein the user'"'"'s influence score is based on a significance of a type of the user'"'"'s acquaintance relationships.

11. The method of claim 10, wherein the computer-implemented social network is at least partially represented using a graph comprising user nodes connected by acquaintance relationships, and wherein a first type of acquaintance relationship that connects a sub-graph portion of the graph to the rest of the graph has a greater significance than a second type of acquaintance relationship that does not connect a sub-graph portion of the graph to the rest of the graph.

12. The method of claim 1, wherein the data representing characteristics of the users relate to an age, a gender, keywords describing interests, or a geographic location.

13. The method of claim 1, further comprising transmitting by the server a list of the ranked of users to the advertiser.

14. The method of claim 1, wherein the bid from the advertiser includes a minimum bid per user, a maximum bid per user, or a total budget for the ad.

15. The method of claim 1, further comprising applying by the server a weighting preference comprising a first weight indicating how much significance to assign to the similarity between the user'"'"'s characteristics and the received characteristics in the ranking of users and a second weight indicating how much significance to assign to the influence score in the ranking of users.

16. The method of claim 15, wherein ranking the users further comprises calculating a first weighted value by applying the first weight to the similarity to the received characteristics for each user, calculating a second weighted value by applying the second weight to the influence score for each user, and combining the first weighted value with the second weighted value.

17. The method of claim 15, wherein the weighting preference is a preference provided by the advertiser.

18. The method of claim 15, wherein the weighting preference is predetermined.

19. The method of claim 15, further comprising calculating by the server a weighting preference based upon a content of the ad, weighting preferences for previous ads with similar content, or an effectiveness of the previous ads.

20. A system for assigning an opportunity to display an ad to users of a social network, comprising:

one or more servers;

an interface to one or more of the servers to receive from an advertiser a request to target an ad to users of a social network, the request comprising data representing characteristics of the users that the advertiser desires to target;

means for ranking the users based on how similar the users'"'"' characteristics are to the received characteristics and an influence score for each user that indicates how influential the user is within the social network;

a request scoring module installed on the one or more servers to score the advertiser'"'"'s request based on a bid from the advertiser for an opportunity to display the ad to one or more of the users targeted by the advertiser; and

an ad assignment module installed on one or more of the servers to;

assign the opportunity to display the ad to the one or more users targeted by the advertiser based on a correlation between a score of the advertiser'"'"'s request and one or more rankings of the one or more users, and

output the ad for display on one or more clients associated with the one or more users assigned to the ad.

21. The system of claim 20, wherein the means for ranking the users generates the influence score for a user based on the user'"'"'s level of activity on a social network.

22. The system of claim 20, wherein the means for ranking the users generates the influence score for a user based on the user'"'"'s acquaintance relationships on the social network.

23. The system of claim 20, wherein the data representing characteristics of the users relate to an age, a gender, interests, or a geographic location of users on a social network.

24. A computer-implemented method comprising:

receiving at a server information related to a content of an ad from an advertiser;

creating by the server an ordered list of users of a computer-implemented social network based on a likelihood a user will be receptive to the content of the ad and an amount of influence a user has over other users of the computer-implemented social network;

receiving at the server a bid from the advertiser for a right to display the ad to a user provided in the ordered list of users;

awarding by the server the right to display the ad to the user to the advertiser if the bid from the advertiser is greater than other bids received within a time period from other advertisers for the right to display the ad to the user, wherein the bid from the advertiser is received within the time period; and

outputting by the server the ad for display on a client associated with the user.

25. The method of claim 24, further comprising determining by the server a likelihood a user of the computer-implemented social network will be receptive to the content of the ad by comparing the content of the ad to information related to interests of the user.

26. The method of claim 24, further comprising determining by the server an amount of influence a user has over other users of the computer-implemented social network by assessing the user'"'"'s relationships with the other users of the computer-implemented social network and the user'"'"'s level of activity on the social network.