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- W2582797034 abstract "To create a sentimental analysis tool for opinion mining of social media data. Information available from social networks is beneficial for analysis of user opinion, for example measuring the feedback on a recently released product, movie or a MOOC, policy change or ongoing events. Using Social network APIs, Python NLTK, automatic collection of a corpus for sentiment analysis and opinion mining purposes is done. Using the corpus we build a sentiment classifier based on Naive Bayes classification that is very accurate, that is able to determine positive, negative and objective sentiments for a document with specificity factor. We also summarize the given input content." @default.
- W2582797034 created "2017-02-03" @default.
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- W2582797034 date "2016-05-01" @default.
- W2582797034 modified "2023-09-23" @default.
- W2582797034 title "Social opinion mining and concise rendition" @default.
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- W2582797034 doi "https://doi.org/10.1109/icaccct.2016.7831718" @default.
- W2582797034 hasPublicationYear "2016" @default.
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