Digital Dissent: An Analysis of the Motivational Contents of Tweets From an Occupy Wall Street Demonstration

Abstract

Social scientific models of protest activity emphasize instrumental motives associated with rational self-interest and beliefs about group efficacy and symbolic motives associated with social identification and anger at perceived injustice. Ideological processes are typically neglected, despite the fact that protest movements occur in a sociopolitical context in which some people are motivated to maintain the status quo, whereas others are motivated to challenge it. To investigate the role of ideology and other social psychological processes in protest participation, we used manual and machine-learning methods to analyze the contents of 23,810 tweets sent on the day of the May Day 2012 Occupy Wall Street demonstration along with an additional 664,937 tweets (sent by 8,244 unique users) during the 2-week lead-up to the demonstration. Results revealed that social identification and liberal ideology were significant independent predictors of protest participation. The effect of social identification was mediated by the expression of collective efficacy, justice concerns, ideological themes, and positive emotion. The effect of liberalism was mediated by the expression of ideological themes, but conservatives were more likely to express ideological backlash against Occupy Wall Street than liberals were to express ideological support for the movement or demonstration. The expression of self-interest and anger was either negatively related or unrelated to protest participation. This work illustrates the promise (and challenge) of using automated methods to analyze new, ecologically valid data sources for studying protest activity and its motivational underpinnings — thereby informing strategic campaigns that employ collective action tactics.