This manuscript critiques industry control and conflicts of interest in academic-industry collaborations in social media research. When academics rely on social media platforms’ classifiers, concepts, and categorization methods, it undermines the replicability of findings. Not disclosing that reliance also impedes meaningful, intersubjective peer review. Industry control over data collection and curation raises concerns about the self-interested goals of industry players in such collaborations, especially when the social media platforms claim the findings are highly policy-relevant. We specifically discuss Meta’s intentional deployment of "break glass" measures—changing the active algorithm to reduce polarization—during data collections in those collaborations. Since none of the original publications explicitly referenced these manipulations, fundamental questions arise about data reliability and transparency
