MAD-TSC: A Multilingual Aligned News Dataset for Target-dependent Sentiment Classification

Evan Dufraisse, Adrian Popescu, Julien Tourille, Armelle Brun, Jerome Deshayes


Abstract
Target-dependent sentiment classification (TSC) enables a fine-grained automatic analysis of sentiments expressed in texts. Sentiment expression varies depending on the domain, and it is necessary to create domain-specific datasets. While socially important, TSC in the news domain remains relatively understudied. We introduce MAD-TSC, a new dataset which differs substantially from existing resources. First, it includes aligned examples in eight languages to facilitate a comparison of performance for individual languages, and a direct comparison of human and machine translation. Second, the dataset is sampled from a diversified parallel news corpus, and is diversified in terms of news sources and geographic spread of entities. Finally, MAD-TSC is more challenging than existing datasets because its examples are more complex. We exemplify the use of MAD-TSC with comprehensive monolingual and multilingual experiments. The latter show that machine translations can successfully replace manual ones, and that performance for all included languages can match that of English by automatically translating test examples.
Anthology ID:
2023.acl-long.461
Volume:
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
July
Year:
2023
Address:
Toronto, Canada
Editors:
Anna Rogers, Jordan Boyd-Graber, Naoaki Okazaki
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
8286–8305
Language:
URL:
https://aclanthology.org/2023.acl-long.461
DOI:
10.18653/v1/2023.acl-long.461
Bibkey:
Cite (ACL):
Evan Dufraisse, Adrian Popescu, Julien Tourille, Armelle Brun, and Jerome Deshayes. 2023. MAD-TSC: A Multilingual Aligned News Dataset for Target-dependent Sentiment Classification. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 8286–8305, Toronto, Canada. Association for Computational Linguistics.
Cite (Informal):
MAD-TSC: A Multilingual Aligned News Dataset for Target-dependent Sentiment Classification (Dufraisse et al., ACL 2023)
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PDF:
https://aclanthology.org/2023.acl-long.461.pdf
Video:
 https://aclanthology.org/2023.acl-long.461.mp4