Hearts for Hating Activists: How Right-Wing Users Polarize TikTok Debates on Climate Protest

This study investigates degrees of polarization in political climate protest debates on TikTok. Drawing on a dataset of automatically transcribed TikTok videos posted by German politicians between 2022 and 2025 (N ≈ 1,700), alongside associated user comments (N ≈ 53,000), this study compares discussions on general climate activism, reformist activism (Fridays for Future), and disruptive activism (Letzte Generation). Using a mixed-method approach that combines Large Language Model–based frame classification, stance detection, and network analysis, this study operationalizes Discursive Polarization across ideological, affective, and interactional dimensions. Findings reveal that while all protest debates on TikTok are polarized, disruptive protests trigger particularly intense attacks, diverting attention away from policy-oriented climate discussions. However, politicians from conservative and far-right parties consistently frame all activists as extremists, criminals, or threats to public order, with far-right accounts dominating both content production and audience support. Network analyses demonstrate that far-right politicians and their supporters form coordinated and highly connected clusters in which both emotionally positive and hostile user engagement reinforces elite-driven antagonism. Even moderate and supportive posts by centrist or left-wing politicians attract disproportionate backlash, illustrating asymmetric polarization dynamics driven by partisan user networks. Overall, the study shows that political TikTok debates around climate protest are consistently polarized along ideological lines, but that disruptiveness intensifies antagonistic engagement and weakens Connective Action among supporters. Most crucially, far-right politicians emerge as the clear beneficiaries of TikTok’s algorithmic affordances, which—coupled with connected outrage that mobilizes their supporters—enable them to dominate debates and entrench Discursive Polarization through Connective Counteraction.