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Volumn 58, Issue , 2016, Pages 83-92

Detection of fake opinions using time series

Author keywords

Fake reviews; Opinion spam; Review spam; Spam detection

Indexed keywords

DATA MINING; INTERNET; ONLINE SYSTEMS; TIME SERIES; WEBSITES;

EID: 84963620321     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2016.03.020     Document Type: Article
Times cited : (98)

References (41)
  • 1
    • 84908032977 scopus 로고    scopus 로고
    • Semi-supervised learning using frequent itemset and ensemble learning for SMS classification
    • Ahmed I., Ali R., Guan D., Lee Y.-K., Lee S., T.C. Chung Semi-supervised learning using frequent itemset and ensemble learning for SMS classification Expert Systems with Applications 42 3 2015 1065 1073
    • (2015) Expert Systems with Applications , vol.42 , Issue.3 , pp. 1065-1073
    • Ahmed, I.1    Ali, R.2    Guan, D.3    Lee, Y.-K.4    Lee, S.5    Chung, T.C.6
  • 2
    • 84900399896 scopus 로고    scopus 로고
    • Opinion fraud detection in online reviews by network effects
    • Akoglu L., Chandy R., Faloutsos C. Opinion fraud detection in online reviews by network effects ICWSM 13 2013 2 11
    • (2013) ICWSM , vol.13 , pp. 2-11
    • Akoglu, L.1    Chandy, R.2    Faloutsos, C.3
  • 6
    • 84860524227 scopus 로고    scopus 로고
    • Biographies, bollywood, boom-boxes and blenders: Domain adaptation for sentiment classification
    • Blitzer J., Dredze M., Pereira F. Biographies, bollywood, boom-boxes and blenders: Domain adaptation for sentiment classification ACL 7 2007 440 447
    • (2007) ACL , vol.7 , pp. 440-447
    • Blitzer, J.1    Dredze, M.2    Pereira, F.3
  • 8
    • 84906330737 scopus 로고    scopus 로고
    • Sentiment analysis based online restaurants fake reviews hype detection
    • Springer International Publishing
    • Deng X., Chen R. Sentiment analysis based online restaurants fake reviews hype detection Web Technologies and Applications 2014 Springer International Publishing 1 10
    • (2014) Web Technologies and Applications , pp. 1-10
    • Deng, X.1    Chen, R.2
  • 12
    • 84900387506 scopus 로고    scopus 로고
    • Exploiting burstiness in reviews for review spammer detection
    • Fei G., Mukherjee A., Liu B., Hsu M., Castellanos M., Ghosh R. Exploiting burstiness in reviews for review spammer detection ICWSM 13 2013 175 184
    • (2013) ICWSM , vol.13 , pp. 175-184
    • Fei, G.1    Mukherjee, A.2    Liu, B.3    Hsu, M.4    Castellanos, M.5    Ghosh, R.6
  • 23
    • 85013754722 scopus 로고    scopus 로고
    • Opinion spam recognition method for online reviews using ontological features
    • Long N.H., Nghia P.H.T., Vuong N.M. Opinion spam recognition method for online reviews using ontological features Tap chí Khoa hoc 61 2014 44
    • (2014) Tap Chí Khoa Hoc , Issue.61 , pp. 44
    • Long, N.H.1    Nghia, P.H.T.2    Vuong, N.M.3
  • 31
    • 84963600466 scopus 로고    scopus 로고
    • Detecting spam review through sentiment analysis
    • Peng Q., Zhong M. Detecting spam review through sentiment analysis Journal of Software 9.8 2014 2065 2072
    • (2014) Journal of Software , vol.9 , Issue.8 , pp. 2065-2072
    • Peng, Q.1    Zhong, M.2
  • 38
    • 84937760391 scopus 로고    scopus 로고
    • Game of information security investment: Impact of attack types and network vulnerability
    • Wu Y., Feng G., Wang N., Liang H. Game of information security investment: Impact of attack types and network vulnerability Expert Systems with Applications 42 15 2015 6132 6146
    • (2015) Expert Systems with Applications , vol.42 , Issue.15 , pp. 6132-6146
    • Wu, Y.1    Feng, G.2    Wang, N.3    Liang, H.4
  • 41
    • 84984636130 scopus 로고    scopus 로고
    • Discovering opinion spammer groups by network footprints
    • Springer International Publishing
    • Ye Junting, Akoglu Leman Discovering opinion spammer groups by network footprints Machine learning and knowledge discovery in databases 2015 Springer International Publishing 267 282
    • (2015) Machine Learning and Knowledge Discovery in Databases , pp. 267-282
    • Ye, J.1    Akoglu, L.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.