Sentiment Analysis From Social Media Content
First Claim
1. A computer-implemented method for sentiment analysis from social media content, comprising:
- crawling, by a processor, a plurality of websites to obtain metadata from social media content;
extracting, by a processor, the metadata from the social media content by identifying a polarity of the sentiment-bearing keywords in a sentence from social media content using a phase transition formula;
determining at least one category corresponding to the at least one sentiment-bearing keyword of the sentence; and
determining at least one sentiment corresponding to the at least one category based on the at least one sentiment-bearing keyword.
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Abstract
The sentiment engine includes a sentiment module configured to gather opinions or determine sentiment expressed in documents, a crawling module configured to crawl servers to obtain at least a subset of the documents or opinions from social media websites, a keyword module configured to extract keywords from documents, a filtering module configured to filter keywords and documents, and a classification module configured to classify documents, sentences, and/or keywords, a polarity prediction module configured to predict the polarity of a sentiment sentence, and a social media net promoter score (SNPS) configured to calculate a loyalty metric of users from social media websites. The functionality of these modules may be combined with one another or in addition to other modules.
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Citations
16 Claims
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1. A computer-implemented method for sentiment analysis from social media content, comprising:
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crawling, by a processor, a plurality of websites to obtain metadata from social media content; extracting, by a processor, the metadata from the social media content by identifying a polarity of the sentiment-bearing keywords in a sentence from social media content using a phase transition formula; determining at least one category corresponding to the at least one sentiment-bearing keyword of the sentence; and determining at least one sentiment corresponding to the at least one category based on the at least one sentiment-bearing keyword. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 15)
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13. A system to determine sentiment expressed in a document, comprising:
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at least one processor; memory; and at least one program stored in the memory, the at least one program comprising instructions to; crawling, by a processor, a plurality of websites to obtain metadata from social media content; extracting, by a processor, the metadata from the social media content by identifying a polarity of the sentiment-bearing keywords in a sentence from social media content using a phase transition formula; determining at least one category corresponding to the at least one sentiment-bearing keyword of the sentence; and determining at least one sentiment corresponding to the at least one category based on the at least one sentiment-bearing keyword. - View Dependent Claims (14)
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16. A computer readable storage medium storing at least one program configured for execution by a computer, the at least one program comprising instructions to:
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crawling, by a processor, a plurality of websites to obtain metadata from social media content; extracting, by a processor, the metadata from the social media content by identifying a polarity of the sentiment-bearing keywords in a sentence from social media content using a phase transition formula; determining at least one category corresponding to the at least one sentiment-bearing keyword of the sentence; and determining at least one sentiment corresponding to the at least one category based on the at least one sentiment-bearing keyword.
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Specification