Improving Online Community Governance at Web Scale

Abstract

Nearly two out of every three people on the planet are members of an an online community, and this number is forecast to keep growing. These communities have an incredible diversity of topic, size, and structure, and they offer unique ways to connect their users and bring people together. Unfortunately, online communities have also been associated with significant offline harms, including the mental health crisis, abuse and harassment, interference with free and democratic elections, and radicalization and political polarization. Almost all online communities rely on some form of governance to set and enforce rules, role model good behavior, and generally lead the community. The forms that this governance takes varies widely from community to community. On some platforms, moderators' work is conducted in the background, while in many others, community leaders are volunteers who take a more visible role. Many communities' governance also relies on a range of complex technical tools. Some communities operate on a pseudodemocratic basis, with nominations and regular elections, while others operate on a consensus model, and still others are effectively autocracies. It is very difficult to know how best to govern an online community, given different community needs, the enormous range of available governance strategies, and the challenge of empirically measuring governance and outcomes. In this dissertation, I conduct research that makes online communities better through data-driven analyses of community values, moderation practices, and experiments with new tools. My work focuses on three important research activities: (1) I \emph{characterize} communities' values in community members' own words to build a foundational understanding of communities' needs and what `better' actually means. (2) I \emph{assess} existing moderation practices and community affordances such as voting at a massive scale across hundreds of thousands of communities in order to identify which practices are most promising. (3) I \emph{deploy} interventions and best practices in partnership with community leaders to maximize real world impact . Much of my research is conducted on Reddit, one of the largest platforms for online communities, and a platform where I am a longtime moderator of several subreddits, and a member of the Reddit Moderator Council. My dissertation makes several key contributions: My theoretical contributions include the first ever taxonomy of community values, based on the largest-to-date surveys of community members. My methodological contributions include a new method for scalably measuring community outcomes by quantifying how community members talk about their moderators, and a new method for classifying the rules enforced by communities. Finally, I make artifact contributions by publishing classifiers for discussions of moderators and rules, and datasets of anonymized survey results, community rules, and news sharing behavior.