Papers with real-world sentiment distribution

1 papers
NewsMTSC: A Dataset for (Multi-)Target-dependent Sentiment Classification in Political News Articles (2021.eacl-main)

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Challenge: Previous work on target-dependent sentiment classification (TSC) has focused on reviews, social media, and other domains where authors tend to express their opinions explicitly.
Approach: They propose a high-quality dataset for TSC on news articles with key differences compared to established datasets.
Outcome: The proposed model improves the state-of-the-art from 81.7 to 83.1 (real-world sentiment distribution) and 82.5 (multi-target sentences) compared to established datasets.

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