@inproceedings{fornaciari-etal-2021-milanlp,
title = "{M}ila{NLP} @ {WASSA}: Does {BERT} Feel Sad When You Cry?",
author = "Fornaciari, Tommaso and
Bianchi, Federico and
Nozza, Debora and
Hovy, Dirk",
editor = "De Clercq, Orphee and
Balahur, Alexandra and
Sedoc, Joao and
Barriere, Valentin and
Tafreshi, Shabnam and
Buechel, Sven and
Hoste, Veronique",
booktitle = "Proceedings of the Eleventh Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis",
month = apr,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.wassa-1.29",
pages = "269--273",
abstract = "The paper describes the MilaNLP team{'}s submission (Bocconi University, Milan) in the WASSA 2021 Shared Task on Empathy Detection and Emotion Classification. We focus on Track 2 - Emotion Classification - which consists of predicting the emotion of reactions to English news stories at the essay-level. We test different models based on multi-task and multi-input frameworks. The goal was to better exploit all the correlated information given in the data set. We find, though, that empathy as an auxiliary task in multi-task learning and demographic attributes as additional input provide worse performance with respect to single-task learning. While the result is competitive in terms of the competition, our results suggest that emotion and empathy are not related tasks - at least for the purpose of prediction.",
}
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%0 Conference Proceedings
%T MilaNLP @ WASSA: Does BERT Feel Sad When You Cry?
%A Fornaciari, Tommaso
%A Bianchi, Federico
%A Nozza, Debora
%A Hovy, Dirk
%Y De Clercq, Orphee
%Y Balahur, Alexandra
%Y Sedoc, Joao
%Y Barriere, Valentin
%Y Tafreshi, Shabnam
%Y Buechel, Sven
%Y Hoste, Veronique
%S Proceedings of the Eleventh Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis
%D 2021
%8 April
%I Association for Computational Linguistics
%C Online
%F fornaciari-etal-2021-milanlp
%X The paper describes the MilaNLP team’s submission (Bocconi University, Milan) in the WASSA 2021 Shared Task on Empathy Detection and Emotion Classification. We focus on Track 2 - Emotion Classification - which consists of predicting the emotion of reactions to English news stories at the essay-level. We test different models based on multi-task and multi-input frameworks. The goal was to better exploit all the correlated information given in the data set. We find, though, that empathy as an auxiliary task in multi-task learning and demographic attributes as additional input provide worse performance with respect to single-task learning. While the result is competitive in terms of the competition, our results suggest that emotion and empathy are not related tasks - at least for the purpose of prediction.
%U https://aclanthology.org/2021.wassa-1.29
%P 269-273
Markdown (Informal)
[MilaNLP @ WASSA: Does BERT Feel Sad When You Cry?](https://aclanthology.org/2021.wassa-1.29) (Fornaciari et al., WASSA 2021)
ACL
- Tommaso Fornaciari, Federico Bianchi, Debora Nozza, and Dirk Hovy. 2021. MilaNLP @ WASSA: Does BERT Feel Sad When You Cry?. In Proceedings of the Eleventh Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, pages 269–273, Online. Association for Computational Linguistics.