Sports, politics, and social media: A human-AI collaborative analysis of consumer reactions to Trump’s Break 50 appearance

What happens when sports, politics, and entertainment collide on social media?

Our study on Donald Trump’s appearance in Break 50 revealed that such intersections did not just generate attention: they sparked a kaleidoscope of interpretations shaped by framing and stereotype perceptions. On YouTube and Instagram, the same event was framed alternately as entertainment, controversy, or athletic performance, each producing strikingly different evaluations of Trump.

Entertainment frames often softened partisanship: awkward fist bumps or missed high-fives were not seen as failures, but as “warm-but-incompetent” moments that made him more relatable. Political frames, by contrast, reignited ideological divides and pushed perceptions toward contempt—even when blended with humor or admiration. Athletic framing centered on competence judgments, which varied across platforms depending on what the medium highlighted (visual performance on YouTube versus curated images on Instagram).

Theoretically, this work shows how framing theory and the Stereotype Content Model stretch when applied to user-generated discourse. Warmth and competence remain central, but in digital environments they are fluid, sometimes contradictory, and always shaped by platform affordances. Methodologically, our human–AI collaboration pipeline, blending topic modeling, reasoning-oriented LLMs, fine-tuning, and embedding analysis, provides a replicable way to make sense of such large-scale meaning-making.

For practitioners, the takeaway is clear: partnering with polarizing figures can amplify both opportunities and risks, depending on how the story is framed and where it circulates. A gaffe in a lighthearted entertainment frame can humanize; in a political frame, it can erode credibility.