Abstract for: Estimating the Dynamics of Individual Opinions in Online Communities
How do opinions change as a result of public interactions and exchange of ideas? How does the proliferation of online media influence these dynamics? While theoretical research provides several hypotheses, empirical analysis of opinion dynamics in online communities is lagging. We develop a unique method for quantifying users’ opinions in a social news website and estimate the decision rules that regulate website visit, story posting, voting, and opinion change. We find evidence for significant and nonlinear opinion change as a result of exposure to near-opinions. We also find evidence of learning as people adjust their activity based on the feedback they receive online and strategic reciprocal voting. Incorporating these decision rules in a simulation model we show the propensity of this online community to converge to the majority opinion, and discuss the underlying mechanisms and implications.