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Volumn , Issue , 2014, Pages 174-179

Evaluating Distant Supervision for Subjectivity and Sentiment Analysis on Arabic Twitter Feeds

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL LINGUISTICS; DATA MINING; SOCIAL NETWORKING (ONLINE); SUPERVISED LEARNING;

EID: 85079102904     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (11)

References (25)
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  • 7
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    • What to do about bad language on the internet
    • Jacob Eisenstein. 2013. What to do about bad language on the internet. In Proceedings of NAACL-HLT, pages 359–369.
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    • Eisenstein, Jacob1
  • 8
    • 79953762206 scopus 로고    scopus 로고
    • Twitter sentiment classification using distant supervision
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    • Alec Go, Richa Bhayani, and Lei Huang. 2009. Twitter sentiment classification using distant supervision. CS224N Project Report, Stanford, pages 1–12.
    • (2009) , pp. 1-12
    • Go, Alec1    Bhayani, Richa2    Huang, Lei3
  • 10
    • 85110334718 scopus 로고    scopus 로고
    • Subjectivity and sentiment analysis of modern standard Arabic and Arabic microblogs
    • Ahmed Mourad and Kareem Darwish. 2013. Subjectivity and sentiment analysis of modern standard Arabic and Arabic microblogs. WASSA 2013, page 55.
    • (2013) WASSA 2013 , pp. 55
    • Mourad, Ahmed1    Darwish, Kareem2
  • 11
    • 80052801287 scopus 로고    scopus 로고
    • MADA+TOKAN: A toolkit for Arabic tokenization, diacritization, morphological disambiguation, pos tagging, stemming and lemmatization
    • Khalid Choukri and Bente Maegaard, editors, Cairo, Egypt, April. The MEDAR Consortium
    • Owen Rambow Nizar Habash and Ryan Roth. 2009. MADA+TOKAN: A toolkit for Arabic tokenization, diacritization, morphological disambiguation, pos tagging, stemming and lemmatization. In Khalid Choukri and Bente Maegaard, editors, Proceedings of the Second International Conference on Arabic Language Resources and Tools, Cairo, Egypt, April. The MEDAR Consortium.
    • (2009) Proceedings of the Second International Conference on Arabic Language Resources and Tools
    • Rambow Nizar Habash, Owen1    Roth, Ryan2
  • 12
    • 85028156346 scopus 로고    scopus 로고
    • Twitter as a corpus for sentiment analysis and opinion mining
    • A. Pak and P. Paroubek. 2010. Twitter as a corpus for sentiment analysis and opinion mining. In Proceedings of LREC.
    • (2010) Proceedings of LREC
    • Pak, A.1    Paroubek, P.2
  • 14
    • 84859916751 scopus 로고    scopus 로고
    • Using emoticons to reduce dependency in machine learning techniques for sentiment classification
    • Association for Computational Linguistics
    • Jonathon Read. 2005. Using emoticons to reduce dependency in machine learning techniques for sentiment classification. In Proceedings of the ACL Student Research Workshop, pages 43–48. Association for Computational Linguistics.
    • (2005) Proceedings of the ACL Student Research Workshop , pp. 43-48
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    • An opinion about opinions about opinions: subjectivity and the aggregate reader
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    • Recognizing contextual polarity: An exploration of features for phrase-level sentiment analysis
    • Theresa Wilson, Janyce Wiebe, and Paul Hoffmann. 2009. Recognizing contextual polarity: An exploration of features for phrase-level sentiment analysis. Computational Linguistics, 35(3):399–433.
    • (2009) Computational Linguistics , vol.35 , Issue.3 , pp. 399-433
    • Wilson, Theresa1    Wiebe, Janyce2    Hoffmann, Paul3
  • 22
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    • Emotional expression online: Gender differences in emoticon use
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.