Abstract
In this paper, we present a Combinatory Categorial Grammar (CCG) based approach to the classification of emotion in microtext. We develop a method that makes use of the notion put forward by Ortony, Clore, and Collins (1988), that emotions are valenced reactions. This hypothesis sits central to our system, in which we adapt contextual valence shifters to infer the emotional content of a text. We integrate this with an augmented version of WordNet-Affect, which acts as our lexicon. Finally, we experiment with a corpus of headlines proposed in the 2007 SemEval Affective Task (Strapparava and Mihalcea 2007) as our microtext corpus, and by taking the other competing systems as a baseline, demonstrate that our approach to emotion categorisation performs favourably.
Original language | English |
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Title of host publication | Analyzing Microtext - Papers from the AAAI Spring Symposium, Technical Report |
Pages | 80-86 |
Number of pages | 7 |
Volume | SS-13-01 |
Publication status | Published - 5 Sept 2013 |
Event | 2013 AAAI Spring Symposium - Palo Alto, CA, United States Duration: 25 Mar 2013 → 27 Mar 2013 |
Conference
Conference | 2013 AAAI Spring Symposium |
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Country/Territory | United States |
City | Palo Alto, CA |
Period | 25/03/13 → 27/03/13 |
ASJC Scopus subject areas
- Artificial Intelligence