Sentiment analysis of Twitter data

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Authors
Yuan, Bo
Issue Date
2016-05
Type
Electronic thesis
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Language
ENG
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Computer science
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Abstract
Sentiment Analysis and Opinion Mining has become a research hot-spot with the rapid development of social network websites.Twitter is a typical social network application with millions of users expressing their sentiment every day. In this work, we explored comprehensively the methodologies applied in sentiment classification over Twitter data: lexicon-based, rule-based and machine learning-based methods. Our data-set is crawled and manually cleaned with the principle of Naturally Annotated Big Data. The data-set contains 20,000 tweets ranging over ten popular topics.
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May 2016
School of Science
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Rensselaer Polytechnic Institute, Troy, NY
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