Extracting semantic orientations of words using spin model
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
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
Topic identification for fine-grained opinion analysis
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Joint extraction of entities and relations for opinion recognition
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 1
Extracting opinions, opinion holders, and topics expressed in online news media text
SST '06 Proceedings of the Workshop on Sentiment and Subjectivity in Text
Automatic emotion classification for interpersonal communication
WASSA '11 Proceedings of the 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis
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We present a system called AESOP that automatically produces affect states associated with characters in a story. This research represents a first step toward the automatic generation of plot unit structures from text. AESOP incorporates several existing sentiment analysis tools and lexicons to evaluate the effectiveness of current sentiment technology on this task. AESOP also includes two novel components: a method for acquiring patient polarity verbs, which impart negative affect on their patients, and affect projection rules to propagate affect tags from surrounding words onto the characters in the story. We evaluate AESOP on a small collection of fables.