Positive unlabeled learning for deceptive reviews detection

EMNLP 2014 - 2014 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference

Volumn , Issue , 2014, Pages 488-498

  Ren, Yafeng ^a   Ji, Donghong ^a   Zhang, Hongbin ^a  

^a WUHAN UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

NATURAL LANGUAGE PROCESSING SYSTEMS; STATISTICS;

GOLD STANDARDS; LDA (LATENT DIRICHLET ALLOCATION); NEGATIVE EXAMPLES; POSITIVE EXAMPLES; RESEARCH COMMUNITIES; SEMI-SUPERVISED; STATE OF THE ART; SVM(SUPPORT VECTOR MACHINE);

SUPPORT VECTOR MACHINES;

EID: 84961288159     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3115/v1/d14-1055     Document Type: Conference Paper

References (28)

1. Alexandros Ntoulas, Marc Najork, Mark Manasse, and Dennis Fetterly. 2006. Detecting spam web pages through content analysis. In Proceedings of the 15th International Conference on World Wide Web, page 83-92, Edinburgh, Scotland.
2. Arjun Mukherjee, Abhinav Kumar, Bing Liu, Junhui Wang, Meichun Hsu, Malu Castellanos, and Riddhiman Ghosh. 2013. Spotting opinion spammers using behavioral footprints. In Proceeding of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Ming, page 632-640, Lyon, France.
3. Arjun Mukherjee, Bing Liu, and Natalie Glance. 2012. Spotting fake reviewer groups in consumer reviews. In Proceeding of the 21st International Conference on World Wide Web, page 191-200, New York, USA.
4. Bing Liu. 2012. Sentiment analysis and opinion mining. Morgan & Claypool Publishers. San Rafael, USA.
5. Bing Liu, Wee Sun Lee, Philip S. Yu, and Xiaoli Li. 2002. Partially supervised classification of text documents. In Proceedings of the 19th International Conference on Machine Learning, page 387-394, San Francisco, USA.
6. Bing Liu, Yang Dai, Xiaoli Li, Wee Sun Lee, and Philip S. Yu. 2003. Building text classifiers using positive and unlabeled examples. In Proceedings of the 3rd IEEE International Conference on Data Ming, page 179-182, Washington, USA.
7. Bo Pang and Lillian Lee. 2008. Opinion mining and sentiment analysis. Foundations and Trends in Information Retrieval, 2(1-2):1-135.
8. Charles Elkan and Keith Noto. 2008. Learning classifiers from only positive and unlabeled data. In Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Ming, page 213-220, Las Vegas, USA.
9. Chirs Buckley, Bgrard Salton, and James Allan. 1994. The effect of adding relevance information in a relevance feedback environment. In Proceedings of the 17th Annual International SIGIR Conference on Research and Development Retrieval, page 292-300, Dublin, Ireland.
10. David M. Blei, Andrew Y. Ng, and Michael I. Jordan. 2003. Latent dirichlet allocation. Journal of Machine Learning Research, 3:993-1022.
11. Dell Zhang. 2005. A simple probabilistic approach to learning from positive and unlabeled examples. In Proceedings of the 5th Annual UK Workshop on Computational Intelligence, page 83-87.
12. Fangtao Li, Minlie Huang, Yi Yang, and Xiaoyan Zhu. 2011. Learning to identify review spam. In Proceeding of the 22nd International Joint Conference on Artificial Intelligence, page 2488-2493, Barcelona, Spain.
13. Fang Wu and Bernardo A. Huberman. 2010. Opinion formation under costly express. ACM Transactions on Intelligence System Technology, 1(5):1-13.
14. Gert R. G. Lanckeriet, Nello Cristianini, Peter Bartlett, Laurent EI Ghaoui, and Michael I.Jordan. 2004. Learning the kernel matrix with seim-difinit programming. Journal of Machine Learning Research, 5:27-72.
15. Harris Drucker, Donghui Wu, and Vladimir N. Vapnik. 1999. Support vector machines for spam categorization. IEEE Transactions on Neural Networks, 10(5):1048-1054.
16. Kumar Ankita and Sminchisescu Cristian. 2006. Support kernel machines for object recognition. In Proceedings of the IEEE 11th International Conference on Computer Vision, page 1-8, Rio de Janeiro, Brzail.
17. Myle Ott, Yelin Choi, Claire Caridie, and Jeffrey T. Hancock. 2011. Finding deceptive opinion spam by any stretch of the imagination. In Proceeding of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technoloies, page 309-319, Portland, USA.
18. Nitin Jindal and Bing Liu. 2008. Opinion spam and analysis. In Proceeding of the 1st ACM International Conference on Web Search and Data Mining, page 137-142, California, USA.
19. Richard Landis and Gary G. Koch. 1977. The measurement of observer agreement for categorical data. Biometrics, 33(1):159-174.
20. Song Feng, Longfei Xing, Anupam Gogar, and Yejin Choi. 2012. Distributional footprints of deceptive product reviews. In Proceeding of the 6th International AAAI Conference on WebBlogs and Social Media, page 98-105, Dublin, Ireland.
21. Song Feng, Ritwik Banerjee, and Yejin Choi. 2012. Syntactic stylometry for deception detection. In Proceeding of the 50th Annual Meeting of the Association for Computational Linguistics, page 171- 175, Jeju Island, Korea.
22. Vladimir N. Vapnik. 1998. Statistical learning theory. Springer. New York, USA.
23. Wanjui Lee, Sergey Verzakov, and Robert P. Duin. 2007. Kernel combination versus classifier combination. In Proceedings of the 7th International Workshop on Multiple Classifier Systems, page 22- 31, Rrague, Czech Republic.
24. Xiaoli Li, Philip S. Yu, Bing Liu, and See Kiong Ng. 2009. Positive unlabeled learning for data stream classification. In Proceedings of the SIAM International Conference on Data Ming, page 257-268, Nevada, USA.
25. Yafeng Ren, Donghong Ji, Lan Yin, and Hongbin Zhang. 2014. Finding deceptive opinion spam by correcting the mislabled instances. Chinese Journal of Electronics, 23(4):702-707.
26. Yafeng Ren, Lan Yin, and Donghong Ji. 2014. Deceptive reviews detection based on language structure and sentiment polarity. Journal of Frontiers of Computer Science and Technology, 8(3):313-320.
27. Yanshan Xiao, Bing Liu, Jie Yin, Longbing Cao, Chengqi Zhang, and Zhifeng Hao. 2011. Similarity-based approach for positive and unlabeled learning. In Proceeding of the 22nd International Joint Conference on Artifical Intelligence, page 1577-1582, Barcelona, Spain.
28. Zoltan Gyongyi, Hector Garcia-Molina, and Jan Pedesen. 2004. Combating web spam web with trustrank. In Proceedings of the 30th International Conference on Very Large Data Bases, page 576- 587, Toronto, Canada.