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This study addresses the challenge of control in open-source software by examining how language functions as a control mechanism in environments without formal authority. Drawing on naturally occurring data from the Linux Kernel project, the research integrates a qualitative meaning analysis with a deep learning-based text classifier. This combined approach enables the mapping of control dynamics within peer-to-peer interactions, revealing distinct facets of control and their interrelations with the linguistic tools inherent to online communities. The analysis identifies key nodes of control, linguistic drivers, and their associations, which are further examined about community-level goals of participation and contribution. Ultimately, the project explores the boundaries and nature of control, shedding light on how independent or loosely affiliated actors enforce control in organizations where traditional employment relationships are absent and diverse objectives coexist.