Sentiment analysis: capturing favorability using natural language processing
Proceedings of the 2nd international conference on Knowledge capture
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
Learning with compositional semantics as structural inference for subsentential sentiment analysis
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Recognition of affect, judgment, and appreciation in text
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
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This paper presents a corpus targeting evaluative meaning as it pertains to descriptions of events. The corpus, POLITICAL-ADS is drawn from 141 television ads from the 2008 U.S. presidential race and contains 3945 NPs and 1549 VPs annotated for scalar sentiment from three different perspectives: the narrator, the annotator, and general society. We show that annotators can distinguish these perspectives reliably and that correlation between the annotator's own perspective and that of a generic individual is higher than those with the narrator. Finally, as a sample application, we demonstrate that a simple compositional model built off of lexical resources outperforms a lexical baseline.