Draft Paper: Understanding the Mechanics of Online Collective Action Using 'Big Data'
Now that so much of collective action takes place online, web-generated data can further understanding of the mechanics of Internet-based mobilization. This 'big data' offers social science researchers the potential for new forms of analysis, using real-time transactional data based on entire populations, rather than sample-based surveys of what people think they did or might do. This paper uses a 'big data' approach to track the growth of over 8,000 petitions to the UK Government on the No. 10 Downing Street website for two years, analyzing the rate of growth per day and testing the hypothesis that the distribution of daily change will be leptokurtic (rather than normal) as previous research on agenda setting would suggest. This hypothesis is confirmed, suggesting that Internet-based mobilization is characterized by tipping points (or punctuated equilibria) and explaining some of the volatility in online collective action. We find also that most successful petitions grow quickly and that the number of signatures a petition receives on its first day is the most significant factor explaining the overall number of signatures a petition receives during its lifetime. These findings could have implications for the strategies of those initiating petitions and the design of web sites with the aim of maximizing citizen engagement with policy issues.
The full draft paper is available on SSRN. We welcome feedback on it.
http://ssrn.com/abstract=2041856 or http://dx.doi.org/10.2139/ssrn.2041856