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license: cc-by-3.0 |
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The SOTA model for Dissonance Detection from the paper [Transfer and Active Learning for Dissonance Detection: Addressing the Rare Class Challenge](https://arxiv.org/abs/2305.02459). |
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RoBERTA-base finetuned on [Dissonance Twitter Dataset](https://github.com/humanlab/dissonance-twitter-dataset), collected from annotating tweets for within-person dissonance. |
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## Dataset Annotation details |
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Tweets were parsed into discourse units, and marked as Belief (Thought or Action) or Other, and pairs of beliefs within the same tweet were relayed to annotators for Dissonance annotation. |
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![annotation process](./annotation_process.jpg) |
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The annotations were conducted on a sheet in the following **dissonance-first** format. |
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![annotation format](./annotation_format.png) |
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The annotators used the following flowchart as a more detailed guide to determining the Dissonance, Consonance and Neither/Other classes: |
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![annotation guidelines](./annotation_guidelines.jpg) |
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