TY - GEN
T1 - A semantic-affective compositional approach for the affective labelling of adjective-noun and noun-noun pairs
AU - Palogiannidi, Elisavet
AU - Iosif, Elias
AU - Koutsakis, Polychronis
AU - Potamianos, Alexandros
N1 - Publisher Copyright:
© 2016 Association for Computational Linguistics
PY - 2016
Y1 - 2016
N2 - Motivated by recent advances in the area of Compositional 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 affective 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.
AB - Motivated by recent advances in the area of Compositional 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 affective 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.
UR - http://www.scopus.com/inward/record.url?scp=85119989348&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85119989348
T3 - Proceedings of the 7th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, WASSA 2016 at the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2016
SP - 154
EP - 160
BT - Proceedings of the 7th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, WASSA 2016 at the 2016 Conference of the North American Chapter of the Association for Computational Linguistics
A2 - Balahur, Alexandra
A2 - van der Goot, Erik
A2 - Vossen, Piek
A2 - Montoyo, Andres
PB - Association for Computational Linguistics (ACL)
T2 - 7th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, WASSA 2016 at the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2016
Y2 - 16 July 2016
ER -