How emotional communication happens in social media: Predicting “Arousal-Homophily-Echo” emotional communication with multi-dimensional features

Abstract

Pervasive emotional expression in cyberspace has increased uncertainties and brought challenges to governance. The occurrence mechanism of emotional communication can provide more ideas to tackle such problems. This study proposed the “Arousal-Homophily-Echo” model with multi-dimensional features as a frame of fine-grained research practice. The model divided Emotional Communication into three levels and we provided their definitions and measurements. Then we creatively combined machine learning and its interpretability to predict and explain how emotional communication happens. The data of the online public discussion on a representative incident was used to fit the prediction models, based on which we summarized important features and analyzed their influences. The optimal prediction models can be utilized to evaluate and monitor crisis communication in cyberspace, while the specific influences of important factors can guide the intervention strategies to alleviate adverse effects of emotional communication.

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