METHOD AND SYSTEM FOR DETERMINING TOPICAL ON-LINE INFLUENCE OF AN ENTITY

• US 20090048904A1
• Filed: 07/16/2008
• Published: 02/19/2009
• Est. Priority Date: 08/16/2007
• Status: Abandoned Application

• Current Assignee: Salesforce.com, Inc.
• Original Assignee: Salesforce.com, Inc.
• Inventors: Newton, Christopher Daniel, Ramsey, Christopher Bennett, Lebrun, Marcel Albert
• Application Number:
  US12/174,345
• Publication Number:
  US 20090048904A1
• Time in Patent Office: Days
• US Class Current: 705/10
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data

Abstract

A method and system for determining topical on-line influence of an entity are disclosed. An influence value of one social media outlet, such as a blog or social networking site, is calculated based on viral properties extracted from publications or posts by the entity through the social media outlet. When the entity has a number of social media outlets associated with it, the topical on-line influence value of the entity is determined based on the influence value of each of the associated social media outlets.

Claims

1. A method for determining topical on-line influence of an entity, comprising the steps of:

(a) matching and tagging content, published by the entity through a social media outlet, with a selected topic;

(b) extracting one or more viral properties from the tagged content;

(c) determining topical on-line influence of the social media outlet according to a first influence model by taking into account the extracted viral properties; and

(d) determining topical on-line influence of the entity according to a second influence model by taking into account the topical on-line influence for one or more social media outlets associated with said entity.

2. The method as described in claim 1, wherein the step (b) comprises:

collecting values of the viral properties for each tagged content; and

aggregating the collected values across the tagged content.

3. The method as described in claim 1, wherein the step (b) comprises:

collecting values of the viral properties at predetermined time intervals; and

storing the collected values in respective time series.

4. 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.

5. The method of claim 1, wherein the step (c) comprises defining the first influence model as a linear combination of the extracted one or more viral properties weighted with respective weights associated with each of the extracted viral properties.

6. The method of claim 1, wherein the step (d) comprises defining the second viral properties as a linear combination of the topical on-line influence of the social media outlets weighted with respective weights associated with each of the social media outlets.

7. The method as described in claim 1 wherein the step (a) comprises selecting the social media outlet from the group consisting of:

a social networking outlet;

a blog outlet;

a video streaming outlet;

an image sharing outlet;

a podcast outlet;

a web analytics outlet;

a peer-to-peer torrent outlet;

a live stream outlet;

a main stream outlet; and

a social news outlet.

8. The method of claim 1, wherein the entity is selected for the group consisting of:

an individual;

an organization; and

a corporation.

9. The method of claim 1, further comprising identifying top influencers, whose topical on-line influence value is above a predetermined threshold, and displaying the results on a computer screen.

10. The method of claim 1 further comprising identifying top movers among entities, comprising determining a speed of change of the topical on-line influence values for the entities, and displaying the results on a computer screen.

20. A computer readable medium, comprising a computer code instructions stored thereon, which, when executed by a computer, perform the steps of the method of claim 1.

11. A method for determining a topical on-line influence, comprising steps of:

(a) defining an entity;

(b) selecting a topic;

(c) selecting a social medial outlet associated with said entity;

(d) retrieving pieces of content posted by said entity from the social media outlet, which match the selected topic;

(e) extracting viral properties of the retrieved pieces of content; and

(f) determining topical on-line influence of the social media outlet based on the extracted viral properties; and

(h) determining a topical on-line influence model of the entity based on the topical on-line influence for one or more social media outlets associated with said entity.

12. The method of claim 11, wherein the step (e) further comprises collecting values of viral properties for each piece of content and aggregating them across all pieces of content.

13. The method of claim 12, wherein the step (f) comprises determining a linear combination of the extracted viral properties weighted with respective weights associated with each of the extracted viral properties.

14. The method of claim 13, wherein the step (h) comprises determining a linear combination of the topical on-line influence of the social media outlets weighted with respective weights associated with each of the social media outlets.

15. The method of claim 11, wherein said one or more social media outlets are selected from the group consisting of a social networking outlet, a blog outlet, a video streaming outlet, an image sharing outlet, a podcast outlet, a web analytics outlet, a peer-to-peer torrent outlet, a live stream outlet, a main stream outlet, and a social news outlet.

16. A system for determining a topical on-line influence of an entity, comprising:

a computer, having a processor and a computer readable medium, storing computer readable instructions, for execution by the processor, to form the following;

(a) a matching module for matching and tagging content to a selected topic said content published by said entity through a social media outlet;

(b) a viral properties extraction module for extracting viral properties from the tagged content;

(c) an outlet influence modeling module for calculating a topical on-line influence for the social media outlet according to an influence model by taking into account the extracted viral properties; and

(d) an entity influence modeling module for calculating the topical on-line influence of the entity according to an influence model by taking into account the topical influence for one or more social media outlets associated to said entity;

the processor processing operations of said matching module, said viral protection extraction module, said outlet influence modeling module and said entity influence modeling module.

17. The system as described in claim 16, wherein the viral protection extraction module comprises a means for collecting values of the viral properties at predetermined time intervals and storing the collected values in respective time series.

18. The system as described in claim 16, further comprising a user interface module for defining the entity, associating the social media outlets with the entity, and assigning weights for each of said viral properties and for each of said social media outlets.

19. The user interface module of claim 19 further comprising means for graphically displaying results of the calculation of the topical on-line influence for the entity.