Advertising based on influence
Advertising based on influence is provided. In some embodiments, advertising based on influence includes determining an influence score (e.g., based on a given dimension) for a subject (e.g., a user), in which the subject is a potential target for an advertisement; and determining targeting of the advertisement based on criteria including the influence score of potential recipients of the advertisement. In some embodiments, the influence score is a directly estimated objective measure of influence (e.g., estimated using a social graph). In some embodiments, advertising based on influence also includes determining pricing of advertisements based on criteria including the influence score of potential recipients of one or more advertisements. In some embodiments, advertising based on influence further includes sharing advertising revenue with the subject based on criteria including the influence score of the first subject (e.g., as an incentive for the subject to view the advertisement).
1. A computer-implemented method, comprising:
determining an influence score for a first subject based on the first subject's association with and influence over other subjects in a social graph representing individuals on Internet by estimating centrality and betweenness by relating the first subject to all subjects linked to the first subject directly or by paths of up to a given length in the social graph, wherein the first subject is a potential target for an advertisement; and
determining targeting of the advertisement based on criteria including the influence score of potential recipients of the advertisement.
2. The method recited in claim 1 , wherein the first subject corresponds to a user.
3. The method recited in claim 1 , wherein the influence score is directly estimated.
4. The method recited in claim 1 , wherein the influence score is a directly estimated objective measure of influence.
5. The method recited in claim 1 , wherein the influence score is an objective influence score.
6. The method recited in claim 1 , wherein the influence score is based on a first dimension.
7. The method recited in claim 1 , wherein the influence score is based on a first dimension, and wherein the targeting of the advertisement is based on the first dimension.
8. The method recited in claim 1 , further comprising:
determining pricing of advertisements based on criteria including the influence score of potential recipients of one or more advertisements.
9. The method recited in claim 1 , further comprising:
sharing advertising revenue with the first subject based on criteria including the influence score of the first subject.
10. The method recited in claim 1 , further comprising:
determining pricing of advertisements based on criteria including the influence score of potential recipients of one or more advertisements; and
sharing advertising revenue with the first subject based on criteria including the influence score of the first subject.
11. The method recited in claim 1 , further comprising:
determining an influence score for a second subject, wherein the second subject is a potential target for an advertisement.
12. The method recited in claim 1 , further comprising:
determining an influence score for a second subject, wherein the second subject is a potential target for an advertisement;
determining pricing of advertisements based on criteria including the influence score of potential recipients of one or more advertisements; and
sharing advertising revenue with the second subject based on criteria including the influence score of the second subject, wherein the second subject is determined to have a higher influence score than the first subject on a first dimension.
13. The method recited in claim 1 , further comprising:
determining an influence score for a plurality of subjects, wherein each of the plurality of subjects is a potential target for an advertisement.
14. The method recited in claim 1 , further comprising:
determining a first influence score for each of a plurality of subjects for a first advertisement, wherein the first advertisement is associated with a first dimension; and
determining a second influence score for each of the plurality of subjects for a second advertisement, wherein the second advertisement is associated with a second dimension.
15. The method recited in claim 1 , further comprising:
determining a first influence score for each of a plurality of subjects for a first advertisement, wherein the first advertisement is associated with a first dimension; and
determining a second influence score for each of the plurality of subjects for a second advertisement, wherein the second advertisement is associated with a second dimension,
wherein the first dimension and the second dimension are the same dimension.
16. The method recited in claim 1 , wherein the influence score is weighted by an expertise score for each subject based on descriptive criteria.
17. The method recited in claim 1 , wherein the influence score is weighted by an expertise score for each subject based on descriptive criteria, wherein the expertise score for each subject is based on the citations from each subject matching descriptive criteria as a relative share of all citations from the subject, wherein each of citation represents an expression of opinion or description by the subject, and citations from all subjects matching the descriptive criteria as a relative share of citations from all subjects.
18. A system, comprising:
a processor configured to:
determine an influence score for a first subject based on the first subject's association with and influence over other subjects in a social graph representing individuals on Internet by estimating centrality and betweenness by relating the first subject to all subjects linked to the first subject directly or by paths of up to a given length in the social graph, wherein the first subject is a potential target for an advertisement; and
determine pricing of the advertisement based on criteria including the influence score of potential recipients of the advertisement; and
a memory coupled to the processor and configured to provide the processor with instructions.
19. The system recited in claim 18 , wherein the processor is further configured to:
determine pricing of the advertisement based on criteria including the influence score of potential recipients of the advertisement; and
share advertising revenue with a subset of the plurality of subjects based on criteria including the influence score of each of the subset of the plurality of subjects as an incentive for viewing the advertisement.
20. A computer program product, the computer program product being embodied in a computer readable storage medium and comprising computer instructions for:
determining an influence score for a first subject based on the first subject's association with and influence over other subjects in a social graph representing individuals on Internet by estimating centrality and betweenness by relating the first subject to all subjects linked to the first subject directly or by paths of up to a given length in the social graph, wherein the first subject is a potential target for an advertisement; and
determining targeting and pricing of the advertisement based on criteria including the influence score of potential recipients of the advertisement.
21. The computer program product recited in claim 20 , further comprising computer instructions for:
sharing advertising revenue at a first proportion with a first subject based on criteria including the influence score of the first subject on a first dimension; and
sharing advertising revenue at a second proportion with a second subject based on criteria including the influence score of the second subject on the first dimension,
wherein the first subject is determined to have a higher influence score than the second subject, and wherein the first proportion is greater than the second proportion.