 One of the most interesting recent uses of the network epistemology framework involves investigating the role of pernicious influencers, especially from industry, on epistemic communities. Holman and Bruner (2015) look at a network model where one agent shares only fraudulent evidence meant to support an inferior theory. As they show, this agent can keep a network from reaching successful consensus by muddying the water with misleading data. Holman and Bruner (2017) and Weatherall et al. (forthcoming) use network epistemology models to explore specific strategies that industry has used to influence scientific research. As Holman and Bruner show, industry can shape the output of a community through “industrial selection”—funding only agents whose methods bias them towards preferred findings. Weatherall et al. add a group of “policy makers” to the model, to show how a propagandist can mislead these public agents simply by sharing a biased sample of the real results produced in an epistemic network. For example, Big Tobacco might gather up real, independent studies that happen to find no link between smoking and cancer, and share these widely (Oreskes and Conway 2011). Together these two papers give insight into how strategies that do not involve fraud can shape scientific research and mislead the public.