WordNet: a lexical database for English
Communications of the ACM
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
Thread detection in dynamic text message streams
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
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
OpinionFinder: a system for subjectivity analysis
HLT-Demo '05 Proceedings of HLT/EMNLP on Interactive Demonstrations
Community Mining from Signed Social Networks
IEEE Transactions on Knowledge and Data Engineering
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Topic and role discovery in social networks with experiments on enron and academic email
Journal of Artificial Intelligence Research
Extracting social networks from literary fiction
ACL '10 Proceedings of the 48th Annual Meeting 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
Clairlib: a toolkit for natural language processing, information retrieval, and network analysis
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: Systems Demonstrations
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This demonstration presents AttitudeMiner, a system for mining attitude from online discussions. AttitudeMiner uses linguistic techniques to analyze the text exchanged between participants of online discussion threads at different levels of granularity: the word level, the sentence level, the post level, and the thread level. The goal of this analysis is to identify the polarity of the attitude the discussants carry towards one another. Attitude predictions are used to construct a signed network representation of the discussion thread. In this network, each discussant is represented by a node. An edge connects two discussants if they exchanged posts. The sign (positive or negative) of the edge is set based on the polarity of the attitude identified in the text associated with the edge. The system can be used in different applications such as: word polarity identification, identifying attitudinal sentences and their signs, signed social network extraction from text, subgroup detect in discussion. The system is publicly available for download and has an online demonstration at http://clair.eecs.umich.edu/AttitudeMiner/.