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NewsMTSC : A Dataset for (Multi-)Target-dependent Sentiment Classification in Political News Articles

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2021

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MERLO, Paola, ed., Jorg TIEDEMANN, ed., Reut TSARFATY, ed.. Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume. Stroudsburg, PA: Association for Computational Linguistics, 2021, pp. 1663-1675

Zusammenfassung

Previous research on target-dependent sentiment classification (TSC) has mostly focused on reviews, social media, and other domains where authors tend to express sentiment explicitly. In this paper, we investigate TSC in news articles, a much less researched TSC domain despite the importance of news as an essential information source in individual and societal decision making. We introduce NewsMTSC, a high-quality dataset for TSC on news articles with key differences compared to established TSC datasets, including, for example, different means to express sentiment, longer texts, and a second test-set to measure the influence of multi-target sentences. We also propose a model that uses a BiGRU to interact with multiple embeddings, e.g., from a language model and external knowledge sources. The proposed model improves the performance of the prior state-of-the-art from F1_m=81.7 to 83.1 (real-world sentiment distribution) and from F1_m=81.2 to 82.5 (multi-target sentences).

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320 Politik

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16th Conference of the European Chapter of the Association for Computational Linguistics (online), 19. Apr. 2021 - 23. Apr. 2021
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ISO 690HAMBORG, Felix, Karsten DONNAY, 2021. NewsMTSC : A Dataset for (Multi-)Target-dependent Sentiment Classification in Political News Articles. 16th Conference of the European Chapter of the Association for Computational Linguistics (online), 19. Apr. 2021 - 23. Apr. 2021. In: MERLO, Paola, ed., Jorg TIEDEMANN, ed., Reut TSARFATY, ed.. Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume. Stroudsburg, PA: Association for Computational Linguistics, 2021, pp. 1663-1675
BibTex
@inproceedings{Hamborg2021NewsM-53815,
  year={2021},
  title={NewsMTSC : A Dataset for (Multi-)Target-dependent Sentiment Classification in Political News Articles},
  url={https://www.aclweb.org/anthology/2021.eacl-main.142/},
  publisher={Association for Computational Linguistics},
  address={Stroudsburg, PA},
  booktitle={Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume},
  pages={1663--1675},
  editor={Merlo, Paola and Tiedemann, Jorg and Tsarfaty, Reut},
  author={Hamborg, Felix and Donnay, Karsten}
}
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https://www.aclweb.org/anthology/2021.eacl-main.142/

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2021-04-30

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