Method and system for determining on-line influence in social media
First Claim
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.
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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.
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Citations
17 Claims
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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:
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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. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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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:
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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. - View Dependent Claims (9, 10, 11, 12, 13)
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14. 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:
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matching and tagging content within a web-site with a selected topic to form tagged content; extracting viral properties for the tagged content; identifying a commentor from said tagged content and an individual cited in the tagged content contained within the web-site; aggregating the viral properties for the tagged content from said web-site to form aggregated viral properties of the tagged content from said web-site, aggregating the viral properties of the tagged content having a comment from said commentor to form aggregated viral properties of the tagged content from said commentor, and aggregating the viral properties of the tagged content citing said individual to form aggregated viral properties of the tagged content citing said individual; computing a 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; computing an influence value of said individual based on a linear combination of the aggregated viral properties of the tagged content citing said individual; and computing a 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.
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15. A system for determining a topical influence of a web-site, comprising:
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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 and tagging content within the web-site to a selected topic to generate tagged content; a viral properties extraction module for extracting viral properties of said tagged content, for identifying a commentor from said tagged content and an individual cited in the tagged content contained within the web-site, for aggregating the viral properties for the tagged content from said web-site to form aggregated viral properties of the tagged content from said web-site, for aggregating the viral properties of the tagged content having a comment from said commentor to form aggregated viral properties of the tagged content from said commentor, and for aggregating the viral properties of the tagged content citing said individual to form aggregated viral properties of the tagged content citing said individual; a commentor influence modeling module for computing a topical influence value of the 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; an individual influence modeling module for computing, based on a linear combination of the aggregated viral properties extracted from the tagged content citing said individual, an influence value of said individual cited in said tagged content; and a site influence modeling module for computing the topical influence value of the web-site based on a linear combination of the aggregated viral properties of the tagged content within the web-site, the topical influence value of the commentor, and the influence value of said individual cited in the tagged content contained; and a database comprising;
a top influential individuals data store for storing the influence value;
a top influential commenters data store for storing the topical influence value of the commentor; and
a top influential sites data store for storing the topical influence value of the web-site. - View Dependent Claims (16, 17)
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Specification