Tweet Analyzer: Identifying Interesting Tweets Based on the Polarity of Tweets
| Autor: | S. Swamynathan, M. Arun Manicka Raja |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Spectrum analyzer
business.industry Computer science Polarity (physics) InformationSystems_INFORMATIONSYSTEMSAPPLICATIONS InformationSystems_INFORMATIONSTORAGEANDRETRIEVAL Sentiment analysis computer.software_genre Classification methods Artificial intelligence InformationSystems_MISCELLANEOUS business computer Natural language processing Sentence |
| Zdroj: | Advances in Intelligent Systems and Computing ISBN: 9788132227328 |
| DOI: | 10.1007/978-81-322-2734-2_31 |
| Popis: | Sentiment analysis is the process of finding the opinions present in the textual content. This paper proposes a tweet analyzer to perform sentiment analysis on twitter data. The work mainly involves the sentiment analysis process using various trained machine learning classifiers applied on large collection of tweets. The classifiers have been trained using maximum number of polarity oriented words for effectively classifying the tweets. The trained classifiers at sentence level outperformed the keyword based classification method. The classified tweets are further analyzed for identifying top N tweets. The experimental results show that the sentiment analyzer system predicted polarities of tweet and effectively identified top N tweets. |
| Databáze: | OpenAIRE |
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