Conference paper
A semantic-affective compositional approach for the affective labelling of adjective-noun and noun-noun pairs
7th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis (WASSA) 2016 (San Diego, CA, 16/06/2016)
2016
Abstract
Motivated by recent advances in the area of Compo-sitional Distributional Semantic Models (CDSMs), we propose a compositional approach for estimating continuous affective ratings for adjective-noun (AN) and noun-noun (NN) pairs. The ratings are computed for the three basic dimensions of continuous affective spaces, namely, valence, arousal and dominance. We propose that similarly to the semantic modification that underlies CDSMs, affective modification may occur within the framework of affec-tive spaces, especially when the constituent words of the linguistic structures under investigation form modifier-head pairs (e.g., AN and NN). The affective content of the entire structure is determined from the interaction between the respective constituents, i.e., the affect conveyed by the head is altered by the modifier. In addition, we investigate the fusion of the proposed model with the semantic-affective model proposed in (Malandrakis et al., 2013) applied both at word-and phrase-level. The automatically computed affective ratings were evaluated against human ratings in terms of correlation. The most accurate estimates are achieved via fusion and absolute performance improvement up to 5% and 4% is reported for NN and AN, respectively.
Details
- Title
- A semantic-affective compositional approach for the affective labelling of adjective-noun and noun-noun pairs
- Authors/Creators
- E. Palogiannidi (Author/Creator)E. Losif (Author/Creator)P. Koutsakis (Author/Creator)A. Potamianos (Author/Creator)
- Conference
- 7th Workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis (WASSA) 2016 (San Diego, CA, 16/06/2016)
- Identifiers
- 991005541258407891
- Murdoch Affiliation
- School of Engineering and Information Technology
- Language
- English
- Resource Type
- Conference paper
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