Temporal Shifts and Causal Interactions of Emotions in Social and Mass Media: A Case Study of the "Reiwa Rice Riot" in Japan
New research reveals how fear on X spreads to news media before hope takes over.
Deep Dive
A new AI study analyzing Japan's 2024 "Reiwa Rice Riot" found emotional shifts on social media consistently preceded those in traditional news. Using machine learning to classify eight basic emotions from X posts and news articles, researchers discovered fear was initially dominant across both platforms. Over time, hope intersected with and ultimately surpassed fear as the prevailing emotion, suggesting social media sentiment can forecast broader societal emotional trajectories.
Why It Matters
This provides a predictive framework for understanding how online emotions cascade into mainstream narratives and real-world events.