Method and system for determining on-line influence in social media

Patent metadata

Field	Value
Publication number	US-9245252-B2
Application number	US-43741809-A
Country	US
Kind code	B2
Filing date	May 7, 2009
Priority date	May 7, 2008
Publication date	Jan 26, 2016
Grant date	Jan 26, 2016

Abstract

A method and system for determining on-line influence in social media is disclosed. A recursive site influence modeling module computes a site influence from aggregated viral properties of content hosted by the site and further integrates, in the formulation of the site influence model, the influence of commentors, commenting on the hosted content, and the influence of individuals cited in the content. The influence of the commentors and individuals is calculated by aggregating viral properties of related content and as well by taking into account the influence of outlets owned by the commentors and the individuals.

First claim

What is claimed is:

1. A computer-implemented method performed by a computer for determining a topical influence value of a commentor, an influence value of an individual and a topical influence value of a web-site, wherein the computer is in communication with a server via network to access a web-site hosted by the server, the computer-implemented method comprising steps of:
matching and tagging content within the web-site with a selected topic, using a processor of the computer, to generate tagged content;
extracting, with the processor, viral properties for the tagged content;
identifying, with the processor, a commentor from said tagged content and an individual cited in the tagged content contained within the web-site;
aggregating, with the processor, the viral properties for the tagged content from said web-site to form aggregated viral properties of the tagged content from said web-site, the viral properties of the tagged content from said commentor to form aggregated viral properties of the tagged content from said commentor, and the viral properties of the tagged content citing said individual to form aggregated viral properties of the tagged content citing said individual;
computing with the processor:
the topical influence value of said commentor based on a linear combination of the aggregated viral properties of the tagged content from said commentor weighted with respective weights applied to each of the aggregated viral properties of the tagged content from said commentor;
the influence value of said individual based on a linear combination of the aggregated viral properties of the tagged content citing said individual; and
the topical influence value of the web-site based on a linear combination of the aggregated viral properties of the tagged content from said web-site, the topical influence value of the commentor, and the influence value of said individual cited in the tagged content.

2. The method of claim 1 , wherein the step of computing, with the processor: the topical influence value of said commentor further comprises:
determining topical influences of on-line outlets owned by said commentor, said topical influences characterized by respective topical influence values of the on-line outlets; and
creating an updated commentor influence model by forming a linear combination of the topical influence values of said on-line outlets and the topical influence value of the commentor.

3. The method of claim 2 , wherein each topical influence of the topical influences of the on-line outlets owned by said commentor is determined from a linear combination of viral properties extracted from a corresponding on-line outlet.

4. The method of claim 1 , further comprising:
repeating the steps of matching and tagging, extracting, identifying, aggregating and computing, the repeating of the computing step including:
updating the topical influence value of said commentor to generate an updated topical influence value of said commentor;
updating the influence value of said individual to generate an updated influence value of said individual; and
updating the topical influence value of the web-site to generate an updated topical influence value of the web-site by integrating the updated topical influence value of the commentor and the updated influence value of said individual in the computation of the updated topical influence value of the web-site.

5. The method of claim 1 , wherein the step of computing the influence value of said individual, further comprises:
identifying an outlet owned by said individual;
calculating an influence value of said outlet owned by said individual based on a linear combination of viral properties extracted from said outlet owned by said individual; and
updating the influence value of said individual based on a linear combination of said aggregated viral properties of the tagged content citing said individual and the influence value of said outlet owned by said individual.

6. The method as described in claim 1 , wherein the step of extracting viral properties for the tagged content comprises:
collecting values of the viral properties at predetermined time intervals; and
storing the collected values in respective time series.

7. The method of claim 1 wherein said viral properties are selected from the group consisting of:
User engagement value;
average Comment count;
average unique commentor count;
cited individual count,
inbound links;
subscribers;
average Social bookmarks;
average Social news votes;
buries;
total count of posts; and
total count of appearance of Individuals names across all posts.

8. A method performed by a computer for determining a topical influence value of a commentor, an influence value of an individual, and a topical influence value of a web-site, wherein the computer is in communication with a server via network to access a web-site hosted by the server, the method comprising the steps of:
matching and tagging content within the web-site with a selected topic, using a processor of the computer, to form tagged content;
extracting, with the processor, viral properties for the tagged content;
identifying from said tagged content, with the processor, a commentor having a comment in said tagged content contained within the web-site and an individual cited in the tagged content contained within the web-site;
aggregating, with the processor, the viral properties for the tagged content from said web-site to form aggregated viral properties of the tagged content from said web-site, the viral properties across all tagged content contained within the web-site including viral properties of the tagged content from said commentor to form aggregated viral properties of the tagged content having the comment from said commentor, and the viral properties of the tagged content citing said individual to form aggregated viral properties of the tagged content citing said individual;
computing, with the processor:
the topical influence value of said commentor using a commentor influence model that is based on a linear combination of the aggregated viral properties of the tagged content having the comment from said commentor, the aggregated viral properties weighted with respective weights applied to each of the aggregated viral properties of the tagged content from said commentor;
the influence value of said individual based on a linear combination of the aggregated viral properties of the tagged content contained within the web-site and citing said individual; and
the topical influence value of the web-site based on a linear combination of the aggregated viral properties of the tagged content from said web-site, the topical influence value of the commentor and the influence value of said individual cited in the tagged content contained within the web-site, said topical influence value of the web-site characterizing the topical on-line influence of the web-site;
repeating the steps of matching and tagging, extracting, identifying, aggregating and computing, the repeating of the computing step including: updating the topical influence value of said commentor using the commentor influence model to generate an updated topical influence value of said commentor; updating the influence value of said individual to generate an updated influence value of said individual; and updating the topical influence value of the web-site to generate an updated topical influence value of the web-site by integrating the updated topical influence value of the commentor and the updated influence value of said individual in the computation of the updated topical influence value of the web-site.

9. The method of claim 8 , wherein the step of computing the topical influence v

Assignees

• Newton Christopher Daniel
• Lebrun Marcel Albert
• Ramsey Christopher Bennett
• Salesforce Com Inc

Inventors

• Newton Christopher Daniel
• Lebrun Marcel Albert
• Ramsey Christopher Bennett

Classifications

• G06Q10/40

  Business processes related to social networking or social networking services · CPC title

• G06Q10/10 Primary

  Office automation; Time management · CPC title

• G06Q30/0201 Primary

  Market modelling; Market analysis; Collecting market data · CPC title

• G06Q10/46

  Determination of level of influence of users within social networking services · CPC title