US2011161270A1PendingUtilityA1

System and method for analyzing electronic message activity

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Individually held — no corporate assignee on recordPriority: Oct 11, 2000Filed: Nov 29, 2010Published: Jun 30, 2011
Est. expiryOct 11, 2020(expired)· nominal 20-yr term from priority
Inventors:Nicholas D. ArnettDavid HoltzmanDavid Pool
G06F 21/6254G06Q 30/0201G06Q 30/02H04L 63/0407H04L 9/40G06F 21/31G06Q 10/10G06F 2221/2117G06Q 30/0204H04L 51/216G06Q 30/0202
49
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Claims

Abstract

Systems and methods for analyzing electronic message activity are disclosed. An example method includes determining a relevancy ranking for each message in a received set of electronic messages, wherein the relevancy ranking indicates whether each message is relevant to a movie, determining an opinion expressed in each message, and computing a prediction of the success of the movie based on the determined opinion for each message.

Claims

exact text as granted — not AI-modified
1 . A method to analyze electronic messages, the method comprising:
 determining a relevancy ranking for each message in a received set of electronic messages, wherein the relevancy ranking indicates whether each message is relevant to a movie;   determining an opinion expressed in each message; and   computing a prediction of the success of the movie based on the determined opinion for each message.   
     
     
         2 . A method as defined in  claim 1 , further comprising comparing a test set of electronic messages about a second movie to data related to the success of the second movie to determine a correlation between the test set of electronic messages and the success of the second movie. 
     
     
         3 . A method as defined in  claim 1 , wherein computing the prediction of the success utilizes the correlation. 
     
     
         4 . A method as defined in  claim 1 , wherein determining the relevancy ranking includes determining that the electronic message is relevant to movies before determining the relevancy ranking of the electronic message for the movie. 
     
     
         5 . A method as defined in  claim 1 , wherein computing the prediction of the success comprises determining at least one of a predicted attendance for the movie, a predicted numbers of sales for the movie, or a predicted revenue for the movie. 
     
     
         6 . A method as defined in  claim 1 , wherein computing the prediction of the success comprises determining a predicted number of downloads of the movie. 
     
     
         7 . A method as defined in  claim 1 , wherein determining the relevancy ranking includes applying a set of rules having weights to the electronic messages. 
     
     
         8 . A method as defined in  claim 7 , wherein one of the rules includes a condition related to a source of the electronic messages. 
     
     
         9 . A method as defined in  claim 1 , wherein one of the rules includes a condition related to words of at least one of a subject or a body of the electronic messages. 
     
     
         10 . A method as defined in  claim 1 , further comprising determining a discussion level for the movie, wherein determining the prediction of the success of the movie is also based on the discussion level. 
     
     
         11 . A computer readable medium storing instructions that, when executed, cause a machine to:
 determine a relevancy ranking for each message in a received set of electronic messages, wherein the relevancy ranking indicates whether each message is relevant to a movie;   determine an opinion expressed in each message; and   compute a prediction of the success of the movie based on the determined opinion for each message.   
     
     
         12 . A method as defined in  claim 1 , further comprising comparing a test set of electronic messages about a second movie to data related to the success of the second movie to determine a correlation between the test set of electronic messages and the success of the second movie. 
     
     
         13 . A method as defined in  claim 1 , wherein computing the prediction of the success utilizes the correlation. 
     
     
         14 . A method as defined in  claim 1 , wherein determining the relevancy ranking includes determining that the electronic message is relevant to movies before determining the relevancy ranking of the electronic message for the movie. 
     
     
         15 . A method as defined in  claim 1 , wherein computing the prediction of the success comprises determining at least one of a predicted attendance for the movie, a predicted numbers of sales for the movie, or a predicted revenue for the movie. 
     
     
         16 . A method as defined in  claim 1 , wherein computing the prediction of the success comprises determining a predicted number of downloads of the movie. 
     
     
         17 . A method as defined in  claim 1 , wherein determining the relevancy ranking includes applying a set of rules having weights to the electronic messages. 
     
     
         18 . A method as defined in  claim 7 , wherein one of the rules includes a condition related to a source of the electronic messages. 
     
     
         19 . A method as defined in  claim 1 , wherein one of the rules includes a condition related to words of at least one of a subject or a body of the electronic messages. 
     
     
         20 . A system to analyze electronic messages, the system comprising:
 a message categorization subsystem to determine a relevancy ranking for each message in a received set of electronic messages, wherein the relevancy ranking indicates whether each message is relevant to a movie;   an opinion rating subsystem to determine an opinion expressed in each message; and   an analysis subsystem to compute a prediction of the success of the movie based on the determined opinion for each message.

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