Analyzing website content or attributes and predicting popularity
First Claim
1. A method comprising:
- computing a first score for a first item that indicates popularity of the first item across all demographics;
computing a second score for a second item that indicates popularity of the second item across all demographics;
wherein the first item and the second item are a same item type;
computing a first impact score that indicates how popular the first item is for a particular demographic relative to other demographics;
computing a second impact score that indicates how popular the second item is for the particular demographic relative to other demographics;
computing a first demographic-specific popularity score for the first item based, at least in part, on the first score and the first impact score;
computing a second demographic-specific popularity score for the second item based, at least in part, on the second score and the second impact score; and
predicting that the particular demographic has a higher interest in the first item than in the second item based on the first demographic-specific popularity score being greater than the second demographic-specific popularity score;
wherein the method is performed by one or more computing devices.
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Abstract
A method to analyze and determine which source content and user interactions are most popular is provided. The method generates scores for items, e.g., articles, topics, authors, or influencers, on a particular source based on data gathered from both the particular source and social media sources. The scores are used to rank items of the same type, and determine which items are the most popular. The method may also take demographic information as input. Using the demographic information, the system may determine the popularity of a particular item in a particular demographic. The method may also predict which demographic an item may be the most popular in. Furthermore, the method may give a recommendation on which author should write on a particular topic, which topic is most likely to be the most popular for a particular demographic, and which influencers should promote the article.
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Citations
28 Claims
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1. A method comprising:
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computing a first score for a first item that indicates popularity of the first item across all demographics; computing a second score for a second item that indicates popularity of the second item across all demographics; wherein the first item and the second item are a same item type; computing a first impact score that indicates how popular the first item is for a particular demographic relative to other demographics; computing a second impact score that indicates how popular the second item is for the particular demographic relative to other demographics; computing a first demographic-specific popularity score for the first item based, at least in part, on the first score and the first impact score; computing a second demographic-specific popularity score for the second item based, at least in part, on the second score and the second impact score; and predicting that the particular demographic has a higher interest in the first item than in the second item based on the first demographic-specific popularity score being greater than the second demographic-specific popularity score; wherein the method is performed by one or more computing devices. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A non-transitory computer-readable medium storing instructions which, when executed by one or more processors, cause performance of a method comprising:
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computing a first score for a first item that indicates popularity of the first item across all demographics; computing a second score for a second item that indicates popularity of the second item across all demographics; wherein the first item and the second item are a same item type; wherein the same item type is one of articles, topics, authors, or influencers; computing a first impact score that indicates how popular the first item is for a particular demographic relative to other demographics; computing a second impact score that indicates how popular the second item is for the particular demographic relative to other demographics; computing a first demographic-specific popularity score for the first item based, at least in part, on the first score and the first impact score; computing a second demographic-specific popularity score for the second item based, at least in part, on the second score and the second impact score; and predicting that the particular demographic has a higher interest in the first item than in the second item based on the first demographic-specific popularity score being greater than the second demographic-specific popularity score. - View Dependent Claims (13, 14, 15, 16, 17, 18, 19, 20, 21)
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22. A computer system comprising:
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a memory; one or more processors coupled to the memory and configured to; compute a first score for a first item that indicates popularity of the first item across all demographics; compute a second score for a second item that indicates popularity of the second item across all demographics; wherein the first item and the second item are a same item type; compute a first impact score that indicates how popular the first item is for a particular demographic relative to other demographics; compute a second impact score that indicates how popular the second item is for the particular demographic relative to other demographics; compute a first demographic-specific popularity score for the first item based, at least in part, on the first score and the first impact score; compute a second demographic-specific popularity score for the second item based, at least in part, on the second score and the second impact score; and predict that the particular demographic has a higher interest in the first item than in the second item based on the first demographic-specific popularity score being greater than the second demographic-specific popularity score. - View Dependent Claims (23, 24, 25, 26, 27, 28)
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Specification