Predicting the semantic orientation of adjectives
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Mining and summarizing customer reviews
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data (Data-Centric Systems and Applications)
Extracting product features and opinions from reviews
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Fully automatic lexicon expansion for domain-oriented sentiment analysis
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
A holistic lexicon-based approach to opinion mining
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
CRO: a system for online review structurization
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Is a Voting Approach Accurate for Opinion Mining?
DaWaK '08 Proceedings of the 10th international conference on Data Warehousing and Knowledge Discovery
A random walk on the red carpet: rating movies with user reviews and pagerank
Proceedings of the 17th ACM conference on Information and knowledge management
VIBES: visualizing changing emotional states in personal stories
SRMC '08 Proceedings of the 2nd ACM international workshop on Story representation, mechanism and context
Studying the effects of noisy text on text mining applications
Proceedings of The Third Workshop on Analytics for Noisy Unstructured Text Data
Classification and Summarization of Pros and Cons for Customer Reviews
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
Domain-specific sentiment analysis using contextual feature generation
Proceedings of the 1st international CIKM workshop on Topic-sentiment analysis for mass opinion
Ontology Based Opinion Mining for Movie Reviews
KSEM '09 Proceedings of the 3rd International Conference on Knowledge Science, Engineering and Management
Opinion analysis of product reviews
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 2
DASA: Dissatisfaction-oriented Advertising based on Sentiment Analysis
Expert Systems with Applications: An International Journal
Sentiment learning on product reviews via sentiment ontology tree
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
SMUC '10 Proceedings of the 2nd international workshop on Search and mining user-generated contents
Structure-aware review mining and summarization
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
ICIC'10 Proceedings of the 6th international conference on Advanced intelligent computing theories and applications: intelligent computing
Journal of Information Science
ELS: a word-level method for entity-level sentiment analysis
Proceedings of the International Conference on Web Intelligence, Mining and Semantics
Target-dependent Twitter sentiment classification
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Sentiment analysis of customer reviews: balanced versus unbalanced datasets
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part I
Topic sentiment analysis in twitter: a graph-based hashtag sentiment classification approach
Proceedings of the 20th ACM international conference on Information and knowledge management
Feature-Based Visual Sentiment Analysis of Text Document Streams
ACM Transactions on Intelligent Systems and Technology (TIST)
Comparison of feature-level learning methods for mining online consumer reviews
Expert Systems with Applications: An International Journal
Experiments with SVM to classify opinions in different domains
Expert Systems with Applications: An International Journal
Discovering business intelligence from online product reviews: A rule-induction framework
Expert Systems with Applications: An International Journal
Opinion and suggestion analysis for expert recommendations
Proceedings of the Workshop on Semantic Analysis in Social Media
Identifying helpful online reviews: A product designer's perspective
Computer-Aided Design
An artificial neural network based approach for sentiment analysis of opinionated text
Proceedings of the 2012 ACM Research in Applied Computation Symposium
Visual boosting in pixel-based visualizations
EuroVis'11 Proceedings of the 13th Eurographics / IEEE - VGTC conference on Visualization
A document-level sentiment analysis approach using artificial neural network and sentiment lexicons
ACM SIGAPP Applied Computing Review
Exploiting social relations for sentiment analysis in microblogging
Proceedings of the sixth ACM international conference on Web search and data mining
Combining user preferences and user opinions for accurate recommendation
Electronic Commerce Research and Applications
Verb Oriented Sentiment Classification
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 01
Roles in social networks: Methodologies and research issues
Web Intelligence and Agent Systems
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Online product reviews are one of the important opinion sources on the Web. This paper studies the problem of determining the semantic orientations (positive or negative) of opinions expressed on product features in reviews. Most existing approaches use a set of opinion words for the purpose. However, the semantic orientations of many words are context dependent. In this paper, we propose to use some linguistic rules to deal with the problem together with a new opinion aggregation function. Extensive experiments show that these rules and the function are highly effective. A system, called Opinion Observer, has also been built.