Learning from positive and unlabeled Amazon reviews: Towards identifying trustworthy reviewers

WWW'12 - Proceedings of the 21st Annual Conference on World Wide Web Companion

Volumn , Issue , 2012, Pages 545-546

  Kokkodis, Marios ^a  

^a NEW YORK UNIVERSITY   (United States)

Author keywords

Positive only learning; Reviewer trustfulness

Indexed keywords

HIGH QUALITY; NEW DIMENSIONS; ONLINE BEHAVIOR; POSITIVE-ONLY LEARNING; PREDICTIVE MODELS; REPUTATION MECHANISM; REVIEW QUALITY; REVIEWER TRUSTFULNESS;

CUSTOMER SATISFACTION;

WORLD WIDE WEB;

EID: 84861073311     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2187980.2188119     Document Type: Conference Paper

References (8)

1. Anindya Ghose and Panagiotis G. Ipeirotis. Estimating the helpfulness and economic impact of product reviews: Mining text and reviewer characteristics. TKDE, 23(10), 2011.
2. Yue Lu, Panayiotis Tsaparas, Alexandros Ntoulas, and Livia Polanyi. Exploiting social context for review quality prediction. In WWW, 2010.
3. Christian Danescu-Niculescu-Mizil, Gueorgi Kossinets, Jon Kleinberg, and Lillian Lee. How opinions are received by online communities: a case study on amazon.com helpfulness votes. In WWW, 2009.
4. Soo-Min Kim, Patrick Pantel, Timothy Chklovski, and Marco Pennacchiotti. Automatically assessing review helpfulness. In EMNLP, 2006.
5. Jingjing Liu, Yunbo Cao, Chin-Yew Lin, Yalou Huang, and Ming Zhou. Low-quality product review detection in opinion summarization. In EMNLP, 2007.
6. Charles Elkan and Keith Noto. Learning classifiers from only positive and unlabeled data. In KDD, 2008.
7. Foster Provost, Brian Dalessandro, Rod Hook, Xiaohan Zhang, and Alan Murray. Audience selection for on-line brand advertising: Privacy-friendly social network targeting. In KDD, 2009.
8. Bing Liu, Yang Dai, Xiaoli Li, Wee Sun Lee, and Philip S. Yu. Building text classifiers using positive and unlaebeled examples. In ICDM, 2003.