| Challenge: | Using unsupervised clustering, we identified seven distinct continuous sentiment trajectories characterized by fluctuations of sentiment throughout a vlog’s narrative time. |
| Approach: | They propose to automatically analyze the vlogs' linguistic styles using a dynamic intra-textual approach to sentiment analysis to shed light on the different temporal trajectories used by vloggers. |
| Outcome: | The proposed method predicts that vlogs with positive endings are the most prevalent in the sample. |
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| Challenge: | . - (EN) |
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| Challenge: | Existing methods for financial sentiment analysis use random splits of a dataset into training and testing to ensure there is no distribution shift between training and deployment. |
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| Challenge: | Existing methods for segmenting user posts into timelines improve quality and cost of manual annotation. |
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DynaSent: A Dynamic Benchmark for Sentiment Analysis (2021.acl-long)
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Identifying Moments of Change from Longitudinal User Text (2022.acl-long)
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The Emotion Dynamics of Literary Novels (2024.findings-acl)
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Towards Robust Sentiment Analysis of Temporally-Sensitive Policy-Related Online Text (2025.acl-srw)
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