Cross-Platform Analysis of Diet Discourse: Scientific Research, News Media, and Social Media Compared

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Abstract

This study investigates how eight popular diets (DASH, Flexitarian, Intermittent Fasting, Keto, Low-FODMAP, Mediterranean, Paleo, and Vegan) are perceived across the modern communication ecosystem. We analyze discourse from academic literature (Web of Science, 1975–2024), mainstream news (The New York Times, 2000–2024), and social media (Reddit, 2005–2022) to understand information flow in a fragmented media landscape. Using time series, engagement, and sentiment analysis on nearly 800,000 documents, we map how diet narratives are constructed and disseminated. Our findings reveal distinct agendas on each platform. Academic and news sources prioritized established diets, while Reddit amplified newer, trend-driven ones. The Mediterranean diet, for instance, dominated scholarly and news coverage but was minimally discussed on Reddit. Intermittent Fasting stood out with synchronized attention across platforms. Monthly bidirectional Granger causality tests on over 200 data points with lags up to 24 months reveal complex, multidirectional predictive relationships. After applying Bonferroni correction for multiple comparisons, Intermittent Fasting exhibits a strong bottom-up dynamic where social media activity predicts both news coverage and scientific literature volume. Conversely, for the Mediterranean diet, traditional news coverage significantly predicts social media discussion, while for the Vegan diet, both social media and scientific literature predict news coverage at different time lags. Sentiment also diverged significantly; scientific discourse was generally positive, while user-generated content was often mixed or negative. For example, the discourse surrounding Veganism on Reddit was notably more negative. This study reveals a fragmented information ecology where scientific consensus does not uniformly dictate public discourse, highlighting the complexity of information flow beyond traditional, top-down models. Our novel, cross-platform framework provides an empirical model for tracking how health topics are constructed and disseminated, revealing the complex, networked interplay between scientific authority, media logic, and user-driven communication

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