Abstract
In this paper, we present a dataset of subjective views (beliefs and attitudes) held by individuals or groups.1 We analyze the usefulness of the dataset by training a neural classifier that identifies belief-containing sentences that are relevant for our broader project of interest—scientific modeling of complex systems. We also explore and discuss difficulties related to annotation of subjective views and propose ways of addressing them.
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CITATION STYLE
Alexeeva, M., Hyland, C. C., Alcock, K., Beal Cohen, A. A., Kanyamahanga, H., Anni, I. K., & Surdeanu, M. (2023). Annotating and Training for Population Subjective Views. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 416–430). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2023.wassa-1.36
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