An Analysis of Diffusion of Universal Basic Income Policy Over Twitter

Iintroduction: Technological advances have increasingly automated tasks that have hitherto been done by humans. Society would benefit from the open discussion of alternative policy approaches, such as Universal Basic Income (UBI), that could alleviate social tensions related to increasing wealth inequality and potential joblessness that have become more problematic due to automation and technological advance. Objective: In this study, we examine the discussion of UBI on Twitter in an effort to understand the types of messages most likely to spread information about policy innovations, and most likely to bring new voices into the discussion. Society would benefit from the open discussion of alternative policy approaches. For example, one such prescription is UBI, which involves giving each citizen above a certain age a set income, regardless of work status or wealth. We have seen the potential for social media sites such as Twitter to draw attention to the grievances of activists in recent social movements. Policy advocates, like political activists, could benefit from research that provides insights into how ideas and messages spread, and ways to grow their audiences. Much work has examined factors related to message diffusion on Twitter. The diffusion of ideas and information can instigate social change. This paper used structuration theory to illustrate how this happens, suggesting that as information flows through our networks it can both re-instantiate and transform social norms. It re-instantiates norms by showing us what we expect to see; what we would think of as normal behavior for a given situation. This framework informs our research questions: 1. Are more retweet event (RTEs) labeled interesting than other types, and specifically, more than resonance? 2. Are tweet messages coded as resonance retweeted more than those coded as interesting? 3. Do RTEs labeled as resonance tend to bring more new users than other types, particularly those labeled interesting? Data: We collect and analyze tweets related to Universal Basic Income and use both content analysis and inferential statistics. We collected Tweets from Twitter’s streaming API using an open source toolkit developed by a co-author. Our collection period spanned from July, 25, 2016 to December 12, 2016, involving 157,832 tweets posted by 35,102 users. Method: The researchers coded a sample of 1000 tweets independently successfully testing for intercoder reliability. Results: The results imply that part of the building of activist networks is the long hard work of trying to get content to spread over weak tie bridges in ways that build one’s audience and reduce the length that information has to flow to reach new potential audiences. Relevance: We apply Roger’s theory of the diffusion of innovations from the field of communication to understand the diffusion of policy ideas on Twitter. Given the recent discussion of the diffusion of fake news, this work is timely as it sheds light on the kinds of messages that diffuse in networks as well as which types of messages tend to bring more new users into a discussion space. We further discuss the impact of Twitter on the policy discussion of Universal Basic Income. This leads to prescriptions for policy advocates wishing to grow their audience and network.