SOCIAL INFLUENCERS DISCOVERY

• US 20120209920A1
• Filed: 03/08/2011
• Published: 08/16/2012
• Est. Priority Date: 02/10/2011
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Neystadt, Eugene (John), Karidi, Ron, Weisfeild, Yitzhak Tzahi, Radinsky, Kira, Varshavsky, Roy, Tennenholtz, Moshe
• Application Number:
  US13/042,463
• Publication Number:
  US 20120209920A1
• Time in Patent Office: Days
• US Class Current: 709/205
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data

Abstract

Social influencers may be identified for specific usage contexts and for influencer type. Influencers may be categorized by mavens, connectors, salesmen, or other categories. Within each usage context, a unified data model may be used to collect data from multiple sources, including multiple social networks, as well as to collect data from different levels of influencers in each usage context. The relevance of various communication media as well as the frequency and quality of use of the media may be factors used to determine a person'"'"'s effectiveness as a specific type of influencer within a usage context.

Claims

1. A method performed on a computer processor, said method comprising:

identifying a plurality of categories;

for each of said categories in said plurality of categories;

retrieve documents from a plurality of communication media;

identify a plurality of persons having expertise in said categories;

for each of said persons, create an influencer profile and determine an expertise rating based on said documents; and

for each of said persons, determine an influencer type and an influencer type strength, and store said influencer type and said influencer type strength in said influencer profile.

2. The method of claim 1, said plurality of categories being defined in a hierarchical tree of categories.

3. The method of claim 2, said expertise rating being assigned to a node of said hierarchical tree.

4. The method of claim 1, said influencer type being one of a group composed of:

maven;

connector; and

salesman.

5. The method of claim 1, said influencer type being a maven identified by a plurality of material produced by said person relating to said usage context.

6. The method of claim 5, said influencer type strength being determined in part by analyzing social network connections for said person.

7. The method of claim 6, said influencer type strength being determined in part by analyzing social network connections for said person in a plurality of social networks.

8. The method of claim 7, said plurality of social networks comprising a first social network with one-way relationships and a second social network with two-way relationships.

9. The method of claim 1, said plurality of communication media comprising media having at least one two-way communication.

10. The method of claim 9, said communication media comprising instant messaging media.

11. The method of claim 1, said plurality of communication media comprising one-way communication.

12. The method of claim 11, said one-way communication being a weblog.

13. A system comprising:

a scanning system that scans an online document source to identify persons that have been active in a first topic;

an analysis tool that analyzes said persons to identify a plurality of persons that meet a set of influencer criteria, said set of influencer criteria being determined for each of a plurality of topics;

said analysis tool that, for each topic in said plurality of topics, determines a ranked list of influencers.

14. The system of claim 13, said document source comprising documents within a social network.

15. The system of claim 14, said document source comprising documents within a plurality of social networks.

16. The system of claim 15, said persons being categorized into a plurality of influencer types for each of said usage contexts.

17. The system of claim 16, one of said influencer types being a connector influencer.

18. A method performed on a computer processor, said method comprising:

identifying a plurality of categories, said categories being defined in a hierarchical tree of categories;

for each of said categories in said plurality of categories;

retrieve documents from a plurality of social networks;

identify a plurality of persons having expertise in said usage context;

for each of said persons, create an influencer profile and determine an expertise rating based on said documents; and

for each of said persons, determine an influencer type and an influencer type strength, and store said influencer type and said influencer type strength in said influencer profile.

19. The method of claim 18, at least one of said social networks comprising one-way relationships.

20. The method of claim 19, at least one of said social networks comprising two-way relationships.