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Measuring the Effect of Influential Messages on Varying Personas
Sun, Chenkai1; Li, Jinning1; Chan, Hou Pong2; Zhai, Cheng Xiang1; Ji, Heng1
2023
Source PublicationProceedings of the Annual Meeting of the Association for Computational Linguistics
Volume2
Pages554-562
AbstractPredicting how a user responds to news events enables important applications such as allowing intelligent agents or content producers to estimate the effect on different communities and revise unreleased messages to prevent unexpected bad outcomes such as social conflict and moral injury. We present a new task, Response Forecasting on Personas for News Media, to estimate the response a persona (characterizing an individual or a group) might have upon seeing a news message. Compared to the previous efforts which only predict generic comments to news, the proposed task not only introduces personalization in the modeling but also predicts the sentiment polarity and intensity of each response. This enables more accurate and comprehensive inference on the mental state of the persona. Meanwhile, the generated sentiment dimensions make the evaluation and application more reliable. We create the first benchmark dataset, which consists of 13,357 responses to 3,847 news headlines from Twitter. We further evaluate the SOTA neural language models with our dataset. The empirical results suggest that the included persona attributes are helpful for the performance of all response dimensions. Our analysis shows that the best-performing models are capable of predicting responses that are consistent with the personas, and as a byproduct, the task formulation also enables many interesting applications in the analysis of social network groups and their opinions, such as the discovery of extreme opinion groups.
URLView the original
Language英語English
Scopus ID2-s2.0-85172225532
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Document TypeConference paper
CollectionUniversity of Macau
Affiliation1.University of Illinois Urbana-Champaign, United States
2.Faculty of Science and Technology, University of Macau, Macao
Recommended Citation
GB/T 7714
Sun, Chenkai,Li, Jinning,Chan, Hou Pong,et al. Measuring the Effect of Influential Messages on Varying Personas[C], 2023, 554-562.
APA Sun, Chenkai., Li, Jinning., Chan, Hou Pong., Zhai, Cheng Xiang., & Ji, Heng (2023). Measuring the Effect of Influential Messages on Varying Personas. Proceedings of the Annual Meeting of the Association for Computational Linguistics, 2, 554-562.
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