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Volumn 1, Issue , 2016, Pages

Election result prediction using Twitter sentiment analysis

Author keywords

Labeling; Sentiment analysis; Text classification; Training data; Twitter; Vader

Indexed keywords

LABELING; LEARNING ALGORITHMS; MACHINE LEARNING; SENTIMENT ANALYSIS; SOCIAL ASPECTS; SOCIAL NETWORKING (ONLINE); SUPPORT VECTOR MACHINES;

EID: 85011034383     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/INVENTIVE.2016.7823280     Document Type: Conference Paper
Times cited : (128)

References (13)
  • 3
    • 85080699815 scopus 로고    scopus 로고
    • Lack of training data in sentiment Classification: Current solutions
    • M. Hajmohammadi, "Lack Of Training Data In Sentiment Classification: Current Solutions", IJRCCT, vol. 1, no. 4, pp. 133-138, 2012.
    • (2012) IJRCCT , vol.1 , Issue.4 , pp. 133-138
    • Hajmohammadi, M.1
  • 8
    • 80955181166 scopus 로고    scopus 로고
    • A two-stage framework for crossdomainsentiment classification
    • Oct
    • Q. Wu and S. B. Tan, "A two-stage framework for crossdomainsentiment classification, "Expert Systems with Applications, vol.38, pp. 14269-14275, Oct 2011.
    • (2011) Expert Systems with Applications , vol.38 , pp. 14269-14275
    • Wu, Q.1    Tan, S.B.2
  • 11
    • 85011050451 scopus 로고    scopus 로고
    • dev.twitter.com, [Online]. Available:, [Accessed: 25- Apr- 2016]
    • "The Streaming APIs Twitter Developers", dev.twitter.com, 2016.[Online]. Available: https://dev.twitter.com/streaming/overview.[Accessed: 25- Apr- 2016].
    • (2016) The Streaming APIs Twitter Developers


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.