An Analytical Emotion Framework of Rumour Threads on Social Media
Rui Xing, Boyang Sun, Kun Zhang, Preslav Nakov, Timothy Baldwin, Jey Han Lau
TL;DR
This paper develops a comprehensive, multi‑aspect analytical framework to study how emotions unfold in rumour threads on online social media. Using EmoLLM to annotate valence, emotion categories, and intensity across three large datasets (PHEME, Twitter15, Twitter16), it analyzes polarity, distribution, transitions, trajectories, and causal relationships between rumours and emotions. Key findings show that rumours trigger more negative emotions and that surprise acts as a bridge to other emotions; pessimism arises from sadness and fear, while optimism stems from joy, love, and trust. The framework demonstrates nuanced, causal insights into emotional dynamics with potential implications for improving rumour detection and understanding online discourse, while acknowledging limitations and ethical considerations.
Abstract
Rumours in online social media pose significant risks to modern society, motivating the need for better understanding of how they develop. We focus specifically on the interface between emotion and rumours in threaded discourses, building on the surprisingly sparse literature on the topic which has largely focused on single aspect of emotions within the original rumour posts themselves, and largely overlooked the comparative differences between rumours and non-rumours. In this work, we take one step further to provide a comprehensive analytical emotion framework with multi-aspect emotion detection, contrasting rumour and non-rumour threads and provide both correlation and causal analysis of emotions. We applied our framework on existing widely-used rumour datasets to further understand the emotion dynamics in online social media threads. Our framework reveals that rumours trigger more negative emotions (e.g., anger, fear, pessimism), while non-rumours evoke more positive ones. Emotions are contagious, rumours spread negativity, non-rumours spread positivity. Causal analysis shows surprise bridges rumours and other emotions; pessimism comes from sadness and fear, while optimism arises from joy and love.