Dynamic influence tracking engine and method

• US 9,720,975 B2
• Filed: 01/30/2013
• Issued: 08/01/2017
• Est. Priority Date: 01/30/2012
• Status: Active Grant

• Current Assignee: Massachusetts Institute of Technology
• Original Assignee: Massachusetts Institute of Technology
• Inventors: Zaman, Tauhid Rashed, Shah, Devavrat D.
• Primary Examiner(s): Ly, Cheyne D
• Application Number:
  US13/754,320
• Publication Number:
  US 20130198205A1
• Time in Patent Office: 1,644 Days
• Field of Search: 707748
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation

Abstract

An engine and method for tracking the influence of an entity operating within a social network are presented. A query containing social network content is received. A database for entries referencing the social network content is searched, and interactions between an entity participating within the social network and the social network content are identified. A dynamic interaction network (DIN) of a plurality of the entities is identified and a dynamic influence score for an entity in the query specific DIN is calculated.

Claims

1. A method for tracking the dynamic influence of an entity operating within a social network with a processor, comprising the steps of:

receiving a query comprising user-generated social network content;

searching a database for entries referencing the social network content;

identifying an interaction between an entity participating within the social network and the social network user-generated content, wherein the interaction comprises proliferating the social network media content to other entities and occurs within a specified time window;

identifying a query specific dynamic interaction network (DIN) comprising a plurality of said entities;

calculating a dynamic influence score for an entity in the query specific DIN,

constructing the query specific DIN using data from the social network that falls within the specified time window and calculating a query specific dynamic influence score for each entity in the query specific DIN, and constructing a global DIN using data from the social network that falls within the specified time window and calculating a global dynamic influence score from the global DIN; and

calculating a global dynamic influence score from the global DIN and combining at least one of the query specific dynamic influence scores and the global dynamic influence score to produce an overall dynamic influence score for each entities in the query specific DIN,

wherein the query specific DIN is constructed using only interactions involving the query, and the dynamic influence score comprises a measure of the reach of an entity with the DIN to proliferate social network media content to other entities, and

wherein the overall dynamic influence scores enable the user to see how influential different entities are on different queries or topics within specific time windows.

2. The method of claim 1, wherein the specified time window is a default time window.

3. The method of claim 1, wherein the specified time window is a query provided time window.

4. The method of claim 1, wherein if the query provides a time window, the specified time window is the query provided time window, otherwise the specified time window is a default time window.

5. The method of claim 1, wherein the dynamic influence score further comprises:

a degree component; and

a reach component.

6. The method of claim 5, wherein the degree component comprises a correlation level between the entity and the social network content.

7. The method of claim 1, further comprising the step of assigning a rank to the entity based in part on the dynamic influence score.

8. The method of claim 1, further comprising the step of displaying the dynamic influence score on a user display interface.

9. The method of claim 1, wherein the query specific DIN includes two or more entities associated with interactions involving the query over a defined time window.

10. The method of claim 9, wherein the two or more entities are schematically represented in the query specific DIN as nodes and wherein the nodes are interconnected based on whether associated entities have an interaction in the social network within the time window.

11. The method of claim 1, further comprising:

in response to receiving the user-provided query and an associated time window, calculating one or more of the dynamic influence scores based on one or more of the query specific DINs; and

returning all content in the social network that matches the query,

wherein the matching content is shown in a display interface, ranked according to the dynamic influence scores of each respective one of the entities that created the returned content.

12. The method of claim 11, wherein each of the dynamic influence scores is based upon rumor centrality with normalization.

13. A method for tracking the dynamic influence of an entity operating within a social network with a processor, comprising the steps of:

receiving a query comprising user-generated social network content;

searching a database for entries referencing the social network content;

identifying an interaction between an entity participating within the social network and the social network user-generated content, wherein the interaction comprises proliferating the social network media content to other entities and occurs within a specified time window;

identifying a query specific dynamic interaction network (DIN) comprising a plurality of said entities;

calculating a dynamic influence score for an entity in the query specific DIN; and

displaying the calculated dynamic influence score with a display interface,

wherein the query specific DIN is constructed using only interactions involving the query, and the dynamic influence score comprises a measure of the reach of an entity with the DIN to proliferate social network media content to other entities,

wherein calculating a dynamic influence score for the entity further comprises;

calculating a first dynamic influence score for the entity within the query specific DIN;

calculating a second dynamic influence score for the entity within a global DIN; and

combining the first dynamic influence score and the second dynamic influence score.

14. Non-transient computer readable media comprising executable instructions for tracking the dynamic influence of an entity operating within a social network with a processor, comprising the steps of:

receiving a query comprising user-generated social network content;

searching a database for entries referencing the social network content;

identifying an interaction between an entity participating within the social network and the social network content, wherein the interaction comprises proliferating the social network media content to other entities and occurs within a specified time window;

identifying a query specific dynamic interaction network (DIN) comprising a plurality of said entities;

calculating a dynamic influence score for an entity in the query specific DIN;

constructing the query specific DIN using data from the social network that falls within the specified time window and calculating a query specific dynamic influence score for each entity in the query specific DIN, and constructing a global DIN using data from the social network that falls within the specified time window and calculating a global dynamic influence score from the global DIN; and

calculating a global dynamic influence score from the global DIN and combining at least one of the query specific dynamic influence scores and the global dynamic influence score to produce an overall dynamic influence score for each entities in the query specific DIN,

wherein the query specific DIN is constructed using only interactions involving the query, and the dynamic influence score comprises a measure of the reach of an entity with the DIN to proliferate social network media content to other entities, and

wherein the overall dynamic influence scores enable the user to see how influential different entities are on different queries or topics within specific time windows.

15. The non-transient media of claim 14, wherein the dynamic influence score further comprises:

a degree component; and

a reach component.

16. The non-transient media of claim 14, further comprising the step of assigning a rank to the entity based in part on the dynamic influence score.

17. Non-transient computer readable media comprising executable instructions for tracking the dynamic influence of an entity operating within a social network with a processor, comprising the steps of:

receiving a query comprising user-generated social network content;

searching a database for entries referencing the social network content;

identifying an interaction between an entity participating within the social network and the social network content, wherein the interaction comprises proliferating the social network media content to other entities and occurs within a specified time window;

identifying a query specific dynamic interaction network (DIN) comprising a plurality of said entities;

calculating a dynamic influence score for an entity in the query specific DIN;

displaying the calculated dynamic influence score with a display interface;

calculating a first dynamic influence score for the entity within the query specific DIN;

calculating a second dynamic influence score for the entity within a global DIN; and

combining the first dynamic influence score and the second dynamic influence score,

wherein the query specific DIN is constructed using only interactions involving the query, and the dynamic influence score comprises a measure of the reach of an entity with the DIN to proliferate social network media content to other entities.