Measurements for Adoption, Spread, and Prediction of Online Human Behavior

The early part of the 21st century saw the creation and quick adoption of social media as a way for people to communicate with their friends and loved ones. In the early days of this new online media, people were generally enthusiastic about this new 'democratic'' way for citizens to express themselves - the beginning of the Arab Spring, in particular, was seen as an example of how social media gave voice to those not in power, and how these combined voices could be used to topple dictators. However, as more people turned to social media for their news, polarization increased as individuals became more isolated from sources that valued nuance and balance. As a consequence, news organizations, social media companies, and government policy makers are now grappling with how to balance questions of free speech with incitement to violence and harassment on social media platforms.

In this dissertation I describe several different methods to understand and describe human behavior on the Internet, and the effect of offline events on online communities. The central focus of this work is a broad investigation into how groups of people behave online. I also present research that seeks to better understand the effect of policies enacted by governments or other social media companies on online behavior. Finally, I provide an alternative to censorship as a way to stop the spread of misinformation and propaganda online as well as preliminary results on this intervention. We use GitHub to research how new information is adopted into a group, and the resulting struggle that emerges from fights over how to apply this new knowledge. The results suggest that censorship has an impact on the structure of groups and that deplatforming results in more frequent users to leave Reddit, for example. Additionally, our results in piloting a social media literacy site suggests that people can be taught to do their own fact checking when they come across misinformation on social media, which we hope will result in less misinformation in the news feeds of citizens and a more informed public.