We’re interested in twitter bots and their interplay with politics.
Can we funnel handles from tweets we archive and see how soon it is before bots take over popular hashtags?
We propose to research this in one or several ways:
Pulling data from R-Shief at periodic intervals, we can run handles through bot-or-not algorithms. We’re curious if they start tapping into popular political hashtags , are there thresholds and percentages of the conversation they take over?
Alternatively, we could create handles that operate as bots from different sides of the political spectrum (pro Trump, “alt-right”, feminist, Hillary supporter, protester) and “fish” for bots by using popular hashtags. After being followed by bots (which we would run through bot-or-not apps) we could analyze their activity on past trending hashtags (like the women’s march) and hashtags which pop off (in reaction to current events, like Trump’s ban, and upcoming exec. orders).
We could create an app that would analyze this data, and possibly make predictions.
- Are there thresholds of hashtag use at which bots will tick up in activity?
- How do bots with different political “ideologies” act differently? (Possibly in comparison to a celebrity bot)