Machine learning of event segmentation for news on demand
Communications of the ACM
Computer
Mining product reputations on the Web
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining the peanut gallery: opinion extraction and semantic classification of product reviews
WWW '03 Proceedings of the 12th international conference on World Wide Web
On an equivalence between PLSI and LDA
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
The Journal of Machine Learning Research
Sentiment analysis: capturing favorability using natural language processing
Proceedings of the 2nd international conference on Knowledge capture
Information diffusion through blogspace
Proceedings of the 13th international conference on World Wide Web
Unifying collaborative and content-based filtering
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Opinion observer: analyzing and comparing opinions on the Web
WWW '05 Proceedings of the 14th international conference on World Wide Web
Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
The predictive power of online chatter
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Using appraisal groups for sentiment analysis
Proceedings of the 14th ACM international conference on Information and knowledge management
Computational Linguistics
Thumbs up?: sentiment classification using machine learning techniques
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
Utility scoring of product reviews
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
A sentimental education: sentiment analysis using subjectivity summarization based on minimum cuts
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Envisioning intelligent information technologies through the prism of web intelligence
Communications of the ACM - Emergency response information systems: emerging trends and technologies
ARSA: a sentiment-aware model for predicting sales performance using blogs
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Show me the money!: deriving the pricing power of product features by mining consumer reviews
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Designing novel review ranking systems: predicting the usefulness and impact of reviews
Proceedings of the ninth international conference on Electronic commerce
Personalized recommendation with adaptive mixture of markov models
Journal of the American Society for Information Science and Technology
Latent class models for collaborative filtering
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Structural topic model for latent topical structure analysis
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
IEEE Transactions on Knowledge and Data Engineering
Probabilistic latent semantic analysis
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Adaptive Bayesian Latent Semantic Analysis
IEEE Transactions on Audio, Speech, and Language Processing
Research challenges and perspectives on Wisdom Web of Things (W2T)
The Journal of Supercomputing
Robust multivariate autoregression for anomaly detection in dynamic product ratings
Proceedings of the 23rd international conference on World wide web
Extracting news blog hot topics based on the W2T Methodology
World Wide Web
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The last decade has seen a rapid growth in the volume of online reviews. A great deal of research has been done in the area of opinion mining, aiming at analyzing the sentiments expressed in those reviews towards products and services. Most of the such work focuses on mining opinions from a collection of reviews posted during a particular period, and does not consider the change in sentiments when the collection of reviews evolve over time. In this paper, we fill in this gap, and study the problem of developing adaptive sentiment analysis models for online reviews. Given the success of latent semantic modeling techniques, we propose two adaptive methods to capture the evolving sentiments. As a case study, we also investigate the possibility of using the extracted adaptive patterns for sales prediction. Our proposal is evaluated on an IMDB dataset consisting of reviews of selected movies and their box office revenues. Experimental results show that the adaptive methods can capture sentiment changes arising from newly available reviews, which helps greatly improve the prediction accuracy.