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Volumn , Issue , 2013, Pages

Sentiment analysis in twitter using machine learning techniques

Author keywords

Machine Learning Techniques; Sentiment Analysis; Twitter

Indexed keywords


EID: 84894446627     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCCNT.2013.6726818     Document Type: Conference Paper
Times cited : (351)

References (17)
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    • A. Balahur, J. M. Hermida, and A. Montoyo, "Building and exploiting emotinet, a knowledge base for emotion detection based on the appraisal theory model," Affective Computing, IEEE Transactions on, vol. 3, no. 1, pp. 88-101, 2012.
    • (2012) Affective Computing, IEEE Transactions on , vol.3 , Issue.1 , pp. 88-101
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  • 9
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    • Sentiment analysis and opinion mining: A survey
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  • 10
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    • On the optimality of the simple bayesian classifier under zero-one loss
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    • Twitter as a corpus for sentiment analysis and opinion mining
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    • Pak, A.1    Paroubek, P.2
  • 16
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    • Ensemble of feature sets and classification algorithms for sentiment classification
    • R. Xia, C. Zong, and S. Li, "Ensemble of feature sets and classification algorithms for sentiment classification," Information Sciences: An International Journal, vol. 181, no. 6, pp. 1138-1152, 2011.
    • (2011) Information Sciences: An International Journal , vol.181 , Issue.6 , pp. 1138-1152
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.