Hendrik Meyer
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hendrikmeyer.bsky.social
Hendrik Meyer
@hendrikmeyer.bsky.social
Research Associate | PhD Candidate | Hamburg University
Political & Climate (Protest) Communication
Website: https://www.hendrik-meyer.com
Google Scholar: https://scholar.google.com/citations?user=j3fDB9oAAAAJ&hl=en
🌄 Limitations & Outlook (follow-up studies are in the making)

– Analysis focused on elites; the fringes of far-right TikTok may look quite different.
– Since EU elections, platform dynamics may have shifted, with other parties (e.g., Die Linke) catching up ahead of the 2025 federal election.
October 7, 2025 at 8:03 AM
⏩ Overall, the AfD generates engagement through divisive frames yet sustains attention — while veiling its radical and extremist positions — by blending established far-right narratives with everyday concerns.
October 7, 2025 at 8:03 AM
– Out-group and migration-related themes appeared less often but still generated strong engagement.

This may reflect ...
(a) a strategic shift toward themes that resonate with citizens, and/or
(b) entrenched exclusionary tropes of 'thick populism' that remain implicit in much of the discourse.
October 7, 2025 at 8:03 AM
❗/💡 Discussion / Interpretation
– Beyond identity-based attacks, the AfD strategically foregrounded real-world concerns that resonate with potential voters ... while still intertwining them with anti-elite cues.
October 7, 2025 at 8:03 AM
– Horizontal protectionism (e.g., migration critique, gender/wokeness) was least frequent (~30%).
– AfD dominance: higher overall engagement rate and far greater output (from accounts with ≥100k lifetime likes) than all other German parties combined.
October 7, 2025 at 8:03 AM
📈 Results: What Was Posted & What Drives Engagement?
– Anti-elitism and out-group attacks generated higher per-video engagement.
– Yet most content leaned toward anti-elite messages or concern-focused themes (economy/inflation, security, rights/freedoms).
October 7, 2025 at 8:03 AM
🧩 Populist Themes & Types (theory-grounded)
We identified 12 themes organized into 3 populist types:

1. Horizontal protectionism (identity/out-group: migrants, “wokeism”)
2. Vertical protectionism (anti-elitism/anti-institutionalism)
3. Concerns of the people (economy/inflation, security, freedoms)
October 7, 2025 at 8:03 AM
🔍 Data & Methods
Timeframe: Mar–Jun 2024
– Content analysis: LLM-enhanced topic modeling (based on 'Concept Induction' by Lam et al., 2024) on 1,271 AfD video transcripts from 54 AfD accounts.
– Engagement comparison: Platform metrics from 109 politicians (5,590 videos in total)
October 7, 2025 at 8:03 AM
❓ Research Interests
– How did AfD politicians use TikTok to communicate populist content during the run-up to the EU elections?
– How did these communication strategies relate to user engagement?
October 7, 2025 at 8:03 AM
3️⃣ This also calls for journalistic self-reflection: Is the broader media sphere amplifying narratives set by right-wing populist actors—even when attempting to deconstruct them?
September 9, 2025 at 10:10 AM
2️⃣ Crucially, when covering LG, the media sphere converges on narratives used mainly by right-wing populist outlets for FFF, even when some outlets aim to critique/deconstruct those narratives.
September 9, 2025 at 10:10 AM
❗ Main takeaways
1️⃣ The protest paradigm intensifies with disruptiveness: event-, criminality-, and extremism-focused coverage crowds out substantive questions of climate justice.
September 9, 2025 at 10:10 AM
- The debate about protest demands recedes when protests are disruptive; extremism/criminality take center stage.
- Qualitative evidence shows that, based on newsroom ideologies, outlets still differ in evaluation and in who the emotional language targets—but the topical focus nonetheless converges.
September 9, 2025 at 10:10 AM
🔎 What we find
- For FFF, frame use and anger align with newsroom ideology: right-leaning outlets stress criminality/extremism; other outlets reference climate justice more often.
- For LG, coverage is more emotionally charged and dominated by criminality/extremism frames across newsroom ideologies.
September 9, 2025 at 10:10 AM
🧪 What we did
- Combined Word2Vec semantic mapping, an anger classifier, and qualitative close reading.
- Identified three salient frames: Global Climate Justice, Criminality, Extremism.
- Modeled outlet differences across the ideological spectrum.
September 9, 2025 at 10:10 AM
➡️ We analyzed 6,632 news articles from 21 German outlets (Jan 2022–May 2023) to compare coverage of Fridays for Future (FFF) and the more disruptive Letzte Generation (LG).
September 9, 2025 at 10:10 AM
Okay, puh --- also kein falscher Link von mir :D
June 23, 2025 at 1:36 PM
Super, dann sind die technical issues auf der Seite wohl gelöst & danke! :)
June 23, 2025 at 1:35 PM
If you’re working with LLMs for text analysis, this framework might serve as a foundation for building your own coding pipeline around LLM-based classification (?) :)
June 23, 2025 at 3:37 AM