Providing context for web articles
First Claim
1. A method for assessing an emotional sentiment related to a topic, comprising:
- identifying first social media content comprising a first link to a first article associated with the topic;
assessing an emotional sentiment related to the first article as a function of one or more terms in the first social media content;
identifying second social media content comprising a second link to a second article associated with the topic and comprising content similar to the first article, the second article comprising content similar to the first article when S(ai,aj)/size(ai) exceeds a predetermined threshold where S(ai,aj) is a number of terms of a largest set of infrequent terms between the first article (ai) and the second article (aj) and size (ai) is the number of terms in the larger of articles ai and aj;
assessing an emotional sentiment related to the second article as a function of one or more terms in the second social media content; and
aggregating the emotional sentiment related to the first article with the emotional sentiment related to the second article to assess the emotional sentiment related to the topic,at least some of the method implemented at least in part via a processing unit.
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Abstract
An overwhelming number of articles are available everyday via the internet. Unfortunately, it is impossible to peruse more than a handful, and it is difficult to ascertain an article'"'"'s social context. The techniques disclosed herein address this problem by harnessing implicit and explicit contextual information from social media. By extracting text surrounding a hyperlink to an article in a post and assessing the article as a function of content surrounding the hyperlink, an article'"'"'s social context is determined and presented. Additionally, articles that are sufficiently similar in content may be grouped to establish a many-to-one relationship between posts and an article, creating a more accurate assessment.
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Citations
20 Claims
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1. A method for assessing an emotional sentiment related to a topic, comprising:
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identifying first social media content comprising a first link to a first article associated with the topic; assessing an emotional sentiment related to the first article as a function of one or more terms in the first social media content; identifying second social media content comprising a second link to a second article associated with the topic and comprising content similar to the first article, the second article comprising content similar to the first article when S(ai,aj)/size(ai) exceeds a predetermined threshold where S(ai,aj) is a number of terms of a largest set of infrequent terms between the first article (ai) and the second article (aj) and size (ai) is the number of terms in the larger of articles ai and aj; assessing an emotional sentiment related to the second article as a function of one or more terms in the second social media content; and aggregating the emotional sentiment related to the first article with the emotional sentiment related to the second article to assess the emotional sentiment related to the topic, at least some of the method implemented at least in part via a processing unit. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A system for assessing an emotional sentiment related to a topic, comprising:
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one or more processing units; and memory comprising instructions that when executed by at least some of the one or more processing units perform operations, comprising; identifying first social media content comprising a first link to a first article associated with the topic; assessing an emotional sentiment related to the first article as a function of one or more terms in the first social media content; identifying second social media content comprising a second link to a second article associated with the topic and comprising content similar to the first article, the second article comprising content similar to the first article when S(ai,aj)/size(ai) exceeds a predetermined threshold, where S(ai,aj) is a number of terms of a largest set of infrequent terms between the first article (ai) and the second article (aj) and size (ai) is the number of terms in the larger of articles ai and aj; assessing an emotional sentiment related to the second article as a function of one or more terms in the second social media content; and aggregating the emotional sentiment related to the first article with the emotional sentiment related to the second article to assess the emotional sentiment related to the topic. - View Dependent Claims (11, 12)
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13. A computer readable storage device comprising computer executable instructions that when executed perform a method for assessing an emotional sentiment related to a topic, comprising:
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identifying first social media content comprising a first link to a first article associated with the topic; assessing an emotional sentiment related to the first article as a function of one or more terms in the first social media content; identifying second social media content comprising a second link to a second article associated with the topic and comprising content similar to the first article, the second article comprising content similar to the first article when S(ai,aj)/size(ai) exceeds a predetermined threshold, where S(ai,aj) is a number of terms of a largest set of infrequent terms between the first article (ai) and the second article (aj) and size (ai) is the number of terms in the larger of articles ai and aj; assessing an emotional sentiment related to the second article as a function of one or more terms in the second social media content; and aggregating the emotional sentiment related to the first article with the emotional sentiment related to the second article to assess the emotional sentiment related to the topic. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20)
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Specification