Learning to recommend helpful hotel reviews
Proceedings of the third ACM conference on Recommender systems
A classification-based review recommender
Knowledge-Based Systems
Exploiting social context for review quality prediction
Proceedings of the 19th international conference on World wide web
A quality-aware model for sales prediction using reviews
Proceedings of the 19th international conference on World wide web
SMUC '10 Proceedings of the 2nd international workshop on Search and mining user-generated contents
Using readability tests to predict helpful product reviews
RIAO '10 Adaptivity, Personalization and Fusion of Heterogeneous Information
A helpfulness modeling framework for electronic word-of-mouth on consumer opinion platforms
ACM Transactions on Intelligent Systems and Technology (TIST)
Automatically predicting peer-review helpfulness
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
Selecting a comprehensive set of reviews
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Understanding differences in perceived peer-review helpfulness using natural language processing
IUNLPBEA '11 Proceedings of the 6th Workshop on Innovative Use of NLP for Building Educational Applications
Multi-facets quality assessment of online opinionated expressions
WISS'10 Proceedings of the 2010 international conference on Web information systems engineering
Automatically ranking reviews based on the ordinal regression model
AICI'11 Proceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part III
Diversifying Product Review Rankings: Getting the Full Picture
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
Text mining and probabilistic language modeling for online review spam detection
ACM Transactions on Management Information Systems (TMIS)
A novel approach for recommending ranked user-generated reviews
AI'10 Proceedings of the 23rd Canadian conference on Advances in Artificial Intelligence
Proceedings of the 2012 ACM international conference on Intelligent User Interfaces
Exploiting shopping and reviewing behavior to re-score online evaluations
Proceedings of the 21st international conference companion on World Wide Web
Recommender systems from "words of few mouths"
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Selecting a characteristic set of reviews
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
What reviews are satisfactory: novel features for automatic helpfulness voting
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Review quality aware collaborative filtering
Proceedings of the sixth ACM conference on Recommender systems
Mining millions of reviews: a technique to rank products based on importance of reviews
Proceedings of the 13th International Conference on Electronic Commerce
Real-time helpfulness prediction based on voter opinions
Concurrency and Computation: Practice & Experience
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
Answering opinion questions on products by exploiting hierarchical organization of consumer reviews
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Identifying helpful online reviews: A product designer's perspective
Computer-Aided Design
Credibility-based product ranking for C2C transactions
Proceedings of the 21st ACM international conference on Information and knowledge management
Have you done anything like that?: predicting performance using inter-category reputation
Proceedings of the sixth ACM international conference on Web search and data mining
Synthetic review spamming and defense
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Using micro-reviews to select an efficient set of reviews
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Context-aware review helpfulness rating prediction
Proceedings of the 7th ACM conference on Recommender systems
Topic extraction from online reviews for classification and recommendation
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Was this review helpful to you?: it depends! context and voting patterns in online content
Proceedings of the 23rd international conference on World wide web
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Online reviews provide a valuable resource for potential customers to make purchase decisions. However, the sheer volume of available reviews as well as the large variations in the review quality present a big impediment to the effective use of the reviews, as the most helpful reviews may be buried in the large amount of low quality reviews. The goal of this paper is to develop models and algorithms for predicting the helpfulness of reviews, which provides the basis for discovering the most helpful reviews for given products. We first show that the helpfulness of a review depends on three important factors: the reviewer’s expertise, the writing style of the review, and the timeliness of the review. Based on the analysis of those factors, we present a nonlinear regression model for helpfulness prediction. Our empirical study on the IMDB movie reviews dataset demonstrates that the proposed approach is highly effective.