Identifying and Filling Gaps in the Conspiracy Theory Literature
This dissertation consists of three chapters. In the first chapter, I employ Luhmann’s orders of observation to organize and identify blind spots that plague the academic literature that studies conspiracy theory and conspiracism. In so doing, I identify two blind spots that I address in the second and third chapters. In the second chapter, I take seriously epistemological research arguing that not all conspiracy theories are dangerous. I develop a framework by which one may approximate the danger associated with mass, serious consideration of particular conspiracy theories. I conclude that mass, serious consideration of most conspiracy theories is not as dangerous as ignoring those conspiracy theories. In the third chapter, I take seriously psychological research arguing that censorship tends to backfire. That research motivates my effort to test the viability allowing un-encumbered discussion of conspiracy theories on social media. I train a Random Forest classifier that estimates the probability that a tweet employs stigma against the conspiracy theory referenced in that tweet. I use the model’s predictions to test whether the stigma associated with conspiracy theory and conspiracism is increasing, whether stigmatizing events cause changes in stigma on Twitter, and whether changes in stigma on Twitter cause changes in retweets for high-stigma tweets relative to low-stigma tweets. I conclude that while non-censorship is unlikely to reduce the spread of conspiracy theories, censorship is also unlikely to reduce the spread of censored conspiracy theories.