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Volumn 8891, Issue , 2014, Pages 108-118

Influence of weak labels for emotion recognition of tweets

Author keywords

Annotation; Crowdsourcing; Emotion recognition; Twitter

Indexed keywords

CROWDSOURCING;

EID: 84915821269     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-319-13817-6_12     Document Type: Conference Paper
Times cited : (5)

References (18)
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    • Bollen, J.1    Mao, H.2    Pepe, A.3
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    • 79957940922 scopus 로고    scopus 로고
    • Using a heterogeneous dataset for emotion analysis in text
    • In: Butz, C., Lingras, P. (eds.), Springer, Heidelberg
    • Chaffar, S., Inkpen, D.: Using a heterogeneous dataset for emotion analysis in text. In: Butz, C., Lingras, P. (eds.) Canadian AI 2011. LNCS, vol. 6657, pp. 62–67. Springer, Heidelberg (2011)
    • (2011) Canadian AI 2011. LNCS , vol.6657 , pp. 62-67
    • Chaffar, S.1    Inkpen, D.2
  • 13
    • 84936113462 scopus 로고    scopus 로고
    • EmpaTweet: Annotating and Detecting Emotions on Twitter
    • Roberts, K., Roach, M.A., Johnson, J.: EmpaTweet: Annotating and Detecting Emotions on Twitter. In: LREC, pp. 3806–3813 (2012)
    • (2012) LREC , pp. 3806-3813
    • Roberts, K.1    Roach, M.A.2    Johnson, J.3
  • 15
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    • Distant supervision for emotion classification with discrete binary values
    • In: Gelbukh, A. (ed.), Springer, Heidelberg
    • Suttles, J., Ide, N.: Distant supervision for emotion classification with discrete binary values. In: Gelbukh, A. (ed.) CICLing 2013, Part II. LNCS, vol. 7817, pp. 121–136. Springer, Heidelberg (2013)
    • (2013) CICLing 2013, Part II. LNCS , vol.7817 , pp. 121-136
    • Suttles, J.1    Ide, N.2
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    • Perspectives on crowdsourcing annotations for natural language processing
    • Wang, A., Hoang, C., Kan, M.: Perspectives on crowdsourcing annotations for natural language processing. Language Resources and Evaluation 47(1), 9–31 (2013)
    • (2013) Language Resources and Evaluation , vol.47 , Issue.1 , pp. 9-31
    • Wang, A.1    Hoang, C.2    Kan, M.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.