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

Abstract

Methods and system are provided for determining a topical influence value of the individual based on aggregated viral properties of tagged content citing the individual. A processor of a computer is used to match content within a web-site with a selected topic and to tag matching content to generate tagged content. Viral properties for the tagged content are extracted, and viral properties of the tagged content citing an individual in the tagged content are aggregated to form aggregated viral properties of the tagged content citing the individual. Based on the aggregated viral properties of the tagged content citing the individual, a topical influence value of the individual can be computed.

1 . A computer-implemented method performed by a computer in communication with a server via network to access a web-site hosted by the server, the computer-implemented method comprising steps of:
 using a processor of the computer to match content within the web-site with a selected topic and to tag matching content to generate tagged content;   extracting, with the processor, viral properties for the tagged content;   aggregating, with the processor, the viral properties of the tagged content citing an individual in the tagged content to form aggregated viral properties of the tagged content citing the individual; and   computing, with the processor, a topical influence value of the individual based on the aggregated viral properties of the tagged content citing the individual.   
     
     
         2 . The computer-implemented method of  claim 1 , further comprising the steps of:
 aggregating, with the processor, the viral properties for the tagged content from the web-site to form aggregated viral properties of the tagged content from the web-site; and   computing, with the processor, a topical influence value of the web-site based on a combination of the aggregated viral properties of the tagged content from the web-site, and the topical influence value of the individual cited in the tagged content.   
     
     
         3 . The computer-implemented method of  claim 2 , 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 the individual to generate an updated topical influence value of the 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 individual in the computation of the updated topical influence value of the web-site. 
   
     
     
         4 . The computer-implemented method of  claim 1 , wherein the step of computing the topical influence value of the individual, further comprises:
 identifying an outlet owned by the individual;   calculating a topical influence value of the outlet owned by the individual based on a combination of viral properties extracted from the outlet owned by the individual; and   updating the topical influence value of the individual based on a combination of the aggregated viral properties of the tagged content citing the individual and the topical influence value of the outlet owned by the individual.   
     
     
         5 . The computer-implemented method as described in  claim 1 , further comprising:
 iterating the steps of matching and tagging, extracting, identifying, aggregating and computing for a plurality of individuals; and   identifying top influential individuals from the plurality of individuals based on the topical influence values for each of the plurality of individuals.   
     
     
         6 . The computer-implemented 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 computer-implemented method of  claim 1 , wherein the viral properties are selected from the group consisting of:
 user engagement value;   cited individual count,   inbound links;   sub scribers;   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 in communication with a server via network to access a web-site hosted by the server, the method comprising the steps of:
 using a processor of the computer to match content within the web-site with a selected topic and to tag matching content to generate tagged content;   extracting, with the processor, viral properties for the tagged content;   aggregating, with the processor, the viral properties across all tagged content contained within the web-site including the viral properties of the tagged content citing the individual in the tagged content to form aggregated viral properties of the tagged content citing the individual;   computing, with the processor, the topical influence value of the individual based on a combination of the aggregated viral properties of the tagged content citing the individual; and   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 the individual to generate an updated topical influence value of the individual.   
     
     
         9 . The method of  claim 8 , further comprising:
 iterating the steps of matching and tagging, extracting, identifying, aggregating and computing for a plurality of individuals; and   identifying top influential individuals from the plurality of individuals based on the topical influence values for each of the plurality of individuals.   
     
     
         10 . The method of  claim 8 , wherein the step of computing the topical influence value of the individual comprises:
 identifying an outlet owned by the individual;   determining an influence of the outlet characterized by a topical influence value of the outlet; and   calculating the topical influence value of the individual by including the topical influence value of the outlet in the combination of the aggregated viral properties of the tagged content citing the individual.   
     
     
         11 . The method of  claim 8 , further comprising:
 aggregating, with the processor, the viral properties for the tagged content from the web-site to form aggregated viral properties of the tagged content from the web-site;   computing, with the processor, the topical influence value of the web-site based on a combination of the aggregated viral properties of the tagged content from the web-site, and the topical influence value of the individual cited in the tagged content, the topical influence value of the web-site characterizing the topical on-line influence of the web-site; and   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 the individual to generate an updated topical influence value of the 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 individual in the computation of the updated topical influence value of the web-site. 
   
     
     
         12 . The method of  claim 11 , further comprising:
 iterating the steps of matching and tagging, extracting, identifying, aggregating and computing for a plurality of web-sites; and   identifying top influential sites based on the topical influence values for each of the plurality of web-sites.   
     
     
         13 . A non-transitory computer readable medium, comprising computer code instructions stored thereon, which, when executed by a computer coupled to a network and in communication with a server via the network to access a web-site hosted by the server, cause the computer to perform the steps of:
 matching content within the web-site with a selected topic and tagging matching content to generate tagged content from the web-site;   extracting viral properties for the tagged content;   aggregating the viral properties of the tagged content citing an individual in the tagged content to form aggregated viral properties of the tagged content from the web-site citing the individual; and   computing a topical influence value of the individual based on a combination of the aggregated viral properties of the tagged content citing the individual.   
     
     
         14 . The non-transitory computer readable medium of  claim 13 , comprising the computer code instructions stored thereon, which, when executed by the computer, further cause the computer to perform the steps of:
 aggregating the viral properties for the tagged content from the web-site to form aggregated viral properties of the tagged content from the web-site; and   computing a topical influence value of the web-site based on a combination of the aggregated viral properties of the tagged content from the web-site, and the topical influence value of the individual cited in the tagged content contained within the web-site.   
     
     
         15 . The non-transitory computer readable medium of  claim 14 , comprising the computer code instructions stored thereon, which, when executed by the computer, further cause the computer to perform the steps of:
 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 the individual to generate an updated topical influence value of the 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 individual in the computation of the updated topical influence value of the web-site. 
   
     
     
         16 . The non-transitory computer readable medium of  claim 12 , comprising the computer code instructions stored thereon, which, when executed by the computer, further cause the computer to perform the steps of:
 identifying an outlet owned by the individual;   calculating a topical influence value of the outlet owned by the individual based on a combination of viral properties extracted from the outlet owned by the individual; and   updating the topical influence value of the individual based on a combination of the aggregated viral properties of the tagged content citing the individual and the topical influence value of the outlet owned by the individual.   
     
     
         17 . The non-transitory computer readable medium of  claim 12 , comprising the computer code instructions stored thereon, which, when executed by the computer, further cause the computer to perform the steps of:
 iterating the steps of matching and tagging, extracting, identifying, aggregating and computing for a plurality of individuals; and   identifying top influential individuals from the plurality of individuals based on the topical influence values for each of the plurality of individuals.   
     
     
         18 . A system, comprising:
 a network;   a server coupled to the network, wherein the server hosts the web-site;   a computer coupled to the network and in communication with the server to access the web-site, the computer comprising:   a processor; and   a computer readable storage medium having computer readable instructions stored thereon for execution by the processor, forming the following modules:
 a content-to-topic matching module for matching content within the web-site with a selected topic and tagging matching content to generate tagged content from the web-site; 
 a viral properties extraction module for: extracting viral properties of the tagged content; and aggregating the viral properties of the tagged content citing the individual to form aggregated viral properties of the tagged content citing the individual; 
 an individual influence modeling module for computing, based on a combination of the aggregated viral properties extracted from the tagged content citing the individual, a topical influence value of the individual cited in the tagged content; and 
   a database comprising: a top influential individuals data store for storing the topical influence value.   
     
     
         19 . The system of  claim 18 , wherein the computer readable storage medium having computer readable instructions stored thereon for execution by the processor further forms:
 a site influence modeling module for computing the topical influence value of the web-site based on a combination of the aggregated viral properties of the tagged content within the web-site, and the topical influence value of the individual cited in the tagged content, and   wherein the database further comprises: a top influential sites data store for storing the topical influence value of the web-site.   
     
     
         20 . The system of  claim 18 , wherein the individual influence modeling module further comprises:
 an individual influence updating module for updating the topical influence of the individual by calculating the topical influence value of the individual based on viral properties extracted from tagged content identifying the individual and topical influence values of outlets owned by the individual.