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Why r/antiwork’s Conversation Endures Beyond the Headlines

17 Jun 2025

Despite media-fueled subscriber surges and a sudden activity crash, r/antiwork’s core discussion topics and heavy user influence remained remarkably stable.

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Spikes, Slumps, and Surprises: Tracking r/antiwork’s Viral Growth and Topic Stability

17 Jun 2025

After media-driven r/antiwork growth, activity spiked then crashed; light users drove posting, but core topics stayed constant despite huge user churn.

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The Data Science Behind r/antiwork’s Upvotes

16 Jun 2025

Reddit r/antiwork posts and comments (2019–2022) were analyzed by user type and media event period using CART for change points and LDA for topic shifts.

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How News Cycles and New Users Shake Up Reddit

16 Jun 2025

This work uniquely quantifies how media-driven surges and controversies shaped r/antiwork, building on studies of Reddit growth, user disruption, and moderation

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Media Hype, Mass Migration, and the Making of an Online Movement

16 Jun 2025

r/antiwork surged during the Great Resignation but collapsed after media backlash; user activity shifted, yet core discussion topics remained consistent.

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Methodological Considerations in Semantic Polarization Research

20 Jun 2024

Dive deep into the appendix of a semantic polarization study, exploring methodological nuances and data analysis approaches in media discourse research.

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Bridging the Partisan Gap: Analyzing Broadcast Media's Role in Political Divide

20 Jun 2024

Discover how linguistic cues in CNN and Fox News shape public perception and contribute to semantic polarization in media discourse

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How Semantic Polarization in Broadcast Media Language Forecasts Semantic Polarity on Social Media

20 Jun 2024

Explore the causal relationship between semantic polarization trends in broadcast media language (CNN and Fox News) and social media discourse.

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Words that Characterize Semantic Polarity between Fox News & CNN in 2020

20 Jun 2024

This study delves into the linguistic differences between CNN and Fox News in 2020, revealing the contextual language differences