Detecting Optimism in Tweets using Knowledge Distillation and Linguistic Analysis of Optimism

Ștefan Cobeli, Ioan-Bogdan Iordache, Shweta Yadav, Cornelia Caragea, Liviu P. Dinu, Dragoș Iliescu

Abstract
Finding the polarity of feelings in texts is a far-reaching task. Whilst the field of natural language processing has established sentiment analysis as an alluring problem, many feelings are left uncharted. In this study, we analyze the optimism and pessimism concepts from Twitter posts to effectively understand the broader dimension of psychological phenomenon. Towards this, we carried a systematic study by first exploring the linguistic peculiarities of optimism and pessimism in user-generated content. Later, we devised a multi-task knowledge distillation framework to simultaneously learn the target task of optimism detection with the help of the auxiliary task of sentiment analysis and hate speech detection. We evaluated the performance of our proposed approach on the benchmark Optimism/Pessimism Twitter dataset. Our extensive experiments show the superior- ity of our approach in correctly differentiating between optimistic and pessimistic users. Our human and automatic evaluation shows that sentiment analysis and hate speech detection are beneficial for optimism/pessimism detection.
Anthology ID:
2022.lrec-1.218
Volume:
Proceedings of the Thirteenth Language Resources and Evaluation Conference
Month:
June
Year:
2022
Address:
Marseille, France
Editors:
Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
2032–2041
Language:
URL:
https://aclanthology.org/2022.lrec-1.218
DOI:
Bibkey:
Cite (ACL):
Ștefan Cobeli, Ioan-Bogdan Iordache, Shweta Yadav, Cornelia Caragea, Liviu P. Dinu, and Dragoș Iliescu. 2022. Detecting Optimism in Tweets using Knowledge Distillation and Linguistic Analysis of Optimism. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, pages 2032–2041, Marseille, France. European Language Resources Association.
Cite (Informal):
Detecting Optimism in Tweets using Knowledge Distillation and Linguistic Analysis of Optimism (Cobeli et al., LREC 2022)
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