Tweets,Triumphs,and Tensions: A Machine Learning Approach to Decoding Multi-Tier Thematic Framing of the 2022 Beijing Winter Olympics on Social Media

Abstract

The current study explored the thematic framing of the 2022 Beijing Winter Olympics on X (Twitter), examining how these thematic frames and audience engagement varied across various content creator tiers—mega, macro, micro, and nano content creators—throughout the year surrounding the event. Through the lens of the framing theory, we employed LDA topic modeling and identified three dominant thematic frames: athletic achievements and competition results, international participation dynamics including boycotts and diplomatic engagements, and geopolitical undertones reflecting on the host nation and global conflicts. A noticeable relationship between thematic frames and engagement levels was observed consistently across creator tiers, with athleticism and contest outcomes garnering sustained attention, underscoring its pivotal role in event discussions. Moreover, our findings revealed unique engagement patterns across creator tiers. Mega creators amplified reactions to sports achievements. Macro creators displayed varied engagement, suggesting responsiveness to ongoing events. Micro creators saw fluctuating engagement with a focus on geopolitical issues. Nano creators actively engaged with both sports achievements and political discussions. Overall, the study illuminates the complexities of media representations and audience perceptions, while dissecting the impactful role played by different tiers of content creators in driving public engagement with a global sporting spectacle.