Measuring praise and criticism: Inference of semantic orientation from association
ACM Transactions on Information Systems (TOIS)
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
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
Label propagation through linear neighborhoods
ICML '06 Proceedings of the 23rd international conference on Machine learning
Extracting semantic orientations of words using spin model
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Determining the sentiment of opinions
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Extracting product features and opinions from reviews
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Recognizing contextual polarity in phrase-level sentiment analysis
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
A tutorial on spectral clustering
Statistics and Computing
Semantic text similarity using corpus-based word similarity and string similarity
ACM Transactions on Knowledge Discovery from Data (TKDD)
Exploring question subjectivity prediction in community QA
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
A computer approach to content analysis: studies using the General Inquirer system
AFIPS '63 (Spring) Proceedings of the May 21-23, 1963, spring joint computer conference
Modeling information-seeker satisfaction in community question answering
ACM Transactions on Knowledge Discovery from Data (TKDD)
A syntactic tree matching approach to finding similar questions in community-based qa services
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Semi-supervised polarity lexicon induction
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Fully automatic lexicon expansion for domain-oriented sentiment analysis
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
FeatureEng '05 Proceedings of the ACL Workshop on Feature Engineering for Machine Learning in Natural Language Processing
Towards the definition of requirements for mixed fact and opinion question answering systems
Proceedings of the 1st international CIKM workshop on Topic-sentiment analysis for mass opinion
Expanding domain sentiment lexicon through double propagation
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Opinion and generic question answering systems: a performance analysis
ACLShort '09 Proceedings of the ACL-IJCNLP 2009 Conference Short Papers
Answering opinion questions with random walks on graphs
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2
Generating high-coverage semantic orientation lexicons from overtly marked words and a thesaurus
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2
The viability of web-derived polarity lexicons
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Identifying text polarity using random walks
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Metadata-aware measures for answer summarization in community Question Answering
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Using graded-relevance metrics for evaluating community QA answer selection
Proceedings of the fourth ACM international conference on Web search and data mining
A generic approach to generate opinion lists of phrases for opinion mining applications
Proceedings of the First International Workshop on Issues of Sentiment Discovery and Opinion Mining
Leveraging relationships in social networks for sentiment analysis
Proceedings of the 18th Brazilian symposium on Multimedia and the web
Mining sentiment terminology through time
Proceedings of the 21st ACM international conference on Information and knowledge management
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Current opinion lexicons contain most of the common opinion words, but they miss slang and so-called urban opinion words and phrases (e.g. delish, cozy, yummy, nerdy, and yuck). These subjectivity clues are frequently used in community questions and are useful for opinion question analysis. This paper introduces a principled approach to constructing an opinion lexicon for community-based question answering (cQA) services. We formulate the opinion lexicon induction as a semi-supervised learning task in the graph context. Our method makes use of existing opinion words to extract new opinion entities (slang and urban words/phrases) from community questions. It then models the opinion entities in a graph context to learn the polarity of the new opinion entities based on the graph connectivity information. In contrast to previous approaches, our method not only learns such polarities from the labeled data but also from the unlabeled data and is more feasible in the web context where the dictionary-based relations (such as synonym, antonym, or hyponym) between most words are not available for constructing a high quality graph. The experiments show that our approach is effective both in terms of the quality of the discovered new opinion entities as well as its ability in inferring their polarity. Furthermore, since the value of opinion lexicons lies in their usefulness in applications, we show the utility of the constructed lexicon in the sentiment classification task.