Exploring linkability of user reviews

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7459 LNCS, Issue , 2012, Pages 307-324

  Almishari, Mishari ^a   Tsudik, Gene ^a  

^a Irvine   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

LINKABILITY; LINKABLE; TECHNIQUES USED;

INFORMATION ANALYSIS; SECURITY OF DATA;

SECURITY SYSTEMS;

EID: 84865595447     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-33167-1_18     Document Type: Conference Paper

References (18)

1. Yelp By The Numbers, http://officialblog.yelp.com/2010/12/2010-yelp-by- the-numbers.html
2. Yelp Elite Squad, http://www.yelp.com/faq#what-is-elite-squad
3. Abbasi, A., Chen, H.: Writeprints: A Stylometric Approach to Identity-Level Identification and Similarity Detection in Cyberspace. ACM Transactions on Information Systems (2008)
4. Bishop, C.M.: Pattern Recognition and Machine Learning. Springer (2006)
5. Dave, K., Lawrence, S., Pennock, D.M.: Mining the Peanut Gallery: Opinion Extraction and Semantic Classification of Product Reviews. In: International Conference on World Wide Web (2003)
6. Hu, M., Liu, B.: Mining and Summarizing Customer Reviews. In: ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2004)
7. Iqbal, F., Binsalleeh, H., Fung, B., Debbabi, M.: A unified data mining solution for authorship analysis in anonymous textual communications. Information Sciences (INS): Special Issue on Data Mining for Information Security (2011)
8. Jindal, N., Liu, B.: Opinion Spam and Analysis. In: ACM International Conference on Web Search and Data Mining (2008)
9. Jindal, N., Liu, B., Lim, E.-P.: Finding Unusual Review Patterns Using Unexpected Rules. In: Proceedings of the 19th ACM International Conference on Information and Knowledge Management (2010)
10. Lewis, D.: Naive(bayes) at forty:the independence assumption in information retrieval. In: Proceedings of the 10th European Conference on Machine Learning (1998)
11. Lim, E.-P., Nguyen, V.-A., Jindal, N., Liu, B., Lauw, H.: Detecting Product Review Spammers using Rating Behaviors. In: Proceedings of the 19th ACM International Conference on Information and Knowledge Management (2010)
12. Mitchell, T.: Machine Learning. McGraw Hill (1997)
13. Nanavati, M., Taylor, N., Aiello, W., Warfield, A.: Herbert West - Deanonymizer. In: 6th USENIX Workshop on Hot Topics in Security (2011)
14. Narayanan, A., Paskov, H., Gong, N.Z., Bethencourt, J., Stefanov, E., Shin, E.C.R., Song, D.: On the Feasibility of Internet-Scale Author Identification. In: IEEE Symposium on Security and Privacy (2012)
15. Pang, B., Lee, L., Vaithyanathan, S.: Thumbs up? Sentiment Classification using Machine Learning Techniques. In: Empirical Methods on Natural Language Processing Conference (2002)
16. Stamatatos, E.: A Survey of Modern Authorship Attribution Methods. Journal of the American Society for Information Science and Technology (2009)
17. Yadav, S., Reddy, A.K., Reddy, A.N., Ranjan, S.: Detecting Algorithmically Generated Malicious Domain Names. In: Internet Measurement Conference (2010)
18. Zheng, R., Li, J., Chen, H., Huang, Z.: A Framework for Authorship Identification of Online Messages: Writing Style Features and Classification Techniques. Journal of the American Society for Information Science and Technology (2006)