Summary: in 2015 I created a Twitter bot, @AnnArborVotes (code on GitHub). (2018 Sam says: after this project ceased I gave the Twitter handle to local civics hero Mary Morgan at A2CivCity). I searched Twitter for 52,000 unique voter names, matching names from the Ann Arbor, MI voter rolls to Twitter accounts based nearby. The bot then tweeted messages to a randomly-selected half of those 2,091 matched individuals, encouraging them to vote in a local primary election that is ordinarily very low-turnout.
I then examined who actually voted (a matter of public record). There was no overall difference between the treatment and control groups. I observed a promising difference in the voting rate when looking only at active Twitter users, i.e., those who had tweeted in the month before I visited their profile. These active users only comprised 7% of my matched voters, however, and the difference in this small subgroup was not statistically significant (n = 150, voting rates of 23% vs 15%, p = 0.28).
I gave a talk summarizing the experiment at Nerd Nite Ann Arbor that is accessible to laypeople (it was at a bar and meant to be entertainment):
This video is hosted by the amazing Ann Arbor District Library – here is their page with multiple formats of this video and a summary of the talk. Here are the slides from the talk (PDF), but they’ll make more sense with the video’s voiceover.
The full write-up:
I love the R programming language (#rstats) and wanted a side project. I’d been curious about Twitter bots. And I’m vexed by how low voter turnout is in local elections. Thus, this experiment.