Helping e-commerce consumers make good purchase decisions: A user reviews-based approach

Lecture Notes in Business Information Processing

Volumn 26 LNBIP, Issue , 2009, Pages 1-10

  Zhang, Richong ^a   Tran, Thomas ^a  

^a UNIVERSITY OF OTTAWA   (Canada)

Author keywords

E Commerce; Information Gain; Online Product Review; Review Helpfulness; Scoring System

Indexed keywords

LEARNING ALGORITHMS; SALES;

E-COMMERCE; INFORMATION GAIN; MACHINE LEARNING TECHNIQUES; NEWSGROUPS; ONLINE PRODUCT REVIEW; ONLINE PRODUCTS; PRODUCT REVIEWS; PURCHASE DECISION; SCORING SYSTEM; SCORING SYSTEMS;

ELECTRONIC COMMERCE;

EID: 67249123758     PISSN: 18651348     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-01187-0_1     Document Type: Conference Paper

References (14)

1. Hatzivassiloglou, V., McKeown, K.R.: Predicting the Semantic Orientation of Adjectives. In: Proceedings of the Eighth Conference on European Chapter of the Association for Com- putational Linguistics, pp. 174-181. Association for Computational Linguistics, Morristown (1997)
2. Hu, M., Liu, B.: Mining and Summarizing Customer Reviews. In: Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2004), pp. 168-177. ACM Press, New York (2004)
3. Hu, N., Liu, L., Zhang, J.: Do Online Reviews Affect Product Sales? The Role of Reviewer Characteristics and Temporal Effects. In: Information Technology and Management (2008)
4. Kim, S.M., Pantel, P., Chklovski, T., Pennacchiotti, M.: Automatically Assessing Review Helpfulness. In: Proceedings of the 2006 Conference on Empirical Methods in Natural Lan- guage Processing, pp. 423-430. Association for Computational Linguistics (2006)
5. Pang, B., Lee, L., Vaithyanathan, S.: Thumbs up?: Sentiment Classi?cation Using Machine Learning Techniques. In: Proceedings of the ACL 2002 conference on Empirical methods in natural language processing (EMNLP 2002), pp. 79-86. Association for Computational Linguistics, Morristown (2002)
6. Park, D.H., Lee, J., Han, I.: The Effect of On-Line Consumer Reviews on Consumer Pur- chasing Intention: The Moderating Role of Involvement. Int. J. Electronic Commerce 11(4), 125-148 (2007)
7. Pollach, I.: Electronic Word of Mouth: A Genre Analysis of Product Reviews on Consumer OpinionWeb Sites. In: HICSS, vol. 3, pp. 1530-1605. IEEE Computer Society, Los Alamitos (2006)
8. Shannon, C.E.: A Mathematical Theory of Communication. SIGMOBILE Mob. Comput. Commun. Rev. 5(1), 3-55 (2001)
9. Turney, P.: Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classi?cation of Reviews, http://citeseer.ist.psu.edu/ turney02thumbs.html
10. Weimer, M., Gurevych, I.: Predicting the Perceived Quality of Web Forum Posts. In: Pro- ceedings of the Conference on Recent Advances in Natural Language Processing, RANLP 2007 (2007)
11. Weimer, M., Gurevych, I., Mühlhäuser, M.: Automatically Assessing the Post Quality in On- line Discussions on Software. In: Proceedings of the 45th Annual Meeting of the Associa- tion for Computational Linguistics, pp. 125-128. Association for Computational Linguistics (2007)
12. Yang, Y., Pedersen, J.O.: A Comparative Study on Feature Selection in Text Categorization. In: Proceedings of the Fourteenth International Conference on Machine Learning (ICML 1997), pp. 412-420. Morgan Kaufmann Publishers Inc., San Francisco (1997)
13. Yu, H., Hatzivassiloglou, V.: Towards Answering Opinion Questions: Separating Facts from Opinions and Identifying the Polarity of Opinion sentences. In: Proceedings of the 2003 Conference on EmpiricalMethods in Natural Language Processing, pp. 129-136. Association for Computational Linguistics, Morristown (2003)
14. Zhuang, L., Jing, F., Zhu, X.Y.: Movie Review Mining and Summarization. In: Proceedings of the 15th ACM International Conference on Information and Knowledge Management (CIKM 2006), pp. 43-50. ACM Press, New York (2006)