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
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Determining the sentiment of opinions
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Eliciting subjectivity and polarity judgements on word senses
HumanJudge '08 Proceedings of the Workshop on Human Judgements in Computational Linguistics
Learning with compositional semantics as structural inference for subsentential sentiment analysis
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
The effect of negation on sentiment analysis and retrieval effectiveness
Proceedings of the 18th ACM conference on Information and knowledge management
Extracting opinions, opinion holders, and topics expressed in online news media text
SST '06 Proceedings of the Workshop on Sentiment and Subjectivity in Text
Semantic frames as an anchor representation for sentiment analysis
WASSA '12 Proceedings of the 3rd Workshop in Computational Approaches to Subjectivity and Sentiment Analysis
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This paper presents a lexicon model for subjectivity description of Dutch verbs that offers a framework for the development of sentiment analysis and opinion mining applications based on a deep syntactic-semantic approach. The model aims to describe the detailed subjectivity relations that exist between the participants of the verbs, expressing multiple attitudes for each verb sense. Validation is provided by an annotation study that shows that these subtle subjectivity relations are reliably identifiable by human annotators.