metadata
license: cc-by-3.0
RoBERTA-base finetuned on our Dissonance Dataset, collected from annotating tweets for within-person dissonance, as described in our paper Transfer and Active Learning for Dissonance Detection: Addressing the Rare Class Challenge.
Dataset Annotation details
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.
The annotations were conducted on a sheet in the following dissonance-first format.
The annotators used the following flowchart as a more detailed guide to determining the Dissonance, Consonance and Neither/Other classes:
