Angel Fernando Garcia Contreras


2023

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Analysis of Style-Shifting on Social Media: Using Neural Language Model Conditioned by Social Meanings
Seiya Kawano | Shota Kanezaki | Angel Fernando Garcia Contreras | Akishige Yuguchi | Marie Katsurai | Koichiro Yoshino
Findings of the Association for Computational Linguistics: EMNLP 2023

In this paper, we propose a novel framework for evaluating style-shifting in social media conversations. Our proposed framework captures changes in an individual’s conversational style based on surprisals predicted by a personalized neural language model for individuals. Our personalized language model integrates not only the linguistic contents of conversations but also non-linguistic factors, such as social meanings, including group membership, personal attributes, and individual beliefs. We incorporate these factors directly or implicitly into our model, leveraging large, pre-trained language models and feature vectors derived from a relationship graph on social media. Compared to existing models, our personalized language model demonstrated superior performance in predicting an individual’s language in a test set. Furthermore, an analysis of style-shifting utilizing our proposed metric based on our personalized neural language model reveals a correlation between our metric and various conversation factors as well as human evaluation of style-shifting.