Papers by Ruopeng An
Towards Robust Sentiment Analysis of Temporally-Sensitive Policy-Related Online Text (2025.acl-srw)
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| Challenge: | Existing methods fail to adequately capture the temporal volatility inherent in policy-related sentiments, arguing that continuous time-series clustering and model merging achieve superior performance. |
| Approach: | They propose to use continuous time-series clustering to select data points for annotation based on temporal trends and then apply model merging techniques. |
| Outcome: | The proposed methods outperform existing methods by an average F1-score of 2.71% on temporally representative data. |