Identifying vulnerable house and senate seats in the 2018 midterm elections
If the last presidential election was any indication, we need new metrics for understanding potential voting behavior. Friends close to the problem say their "experience with [traditional political wonks] has been that the answer is always that somebody tried that once and nobody paid attention and they wandered off" -- so there's plenty of room for experimentation and improvement. The Election Transparency project had success finding new and novel explanations for voter behavior in national elections, and now we'd like to try it out for senate and congressional races.
Working from a foundation of historical results and census data, we'll pull in social media data (and whatever else we come up with) to get a sense of which congressional and senate seats could flip from one party to the other in the 2018 elections.
New methodologies for identifying vulnerable races are valuable to campaigns on both sides of the aisle, and as an open, transparent community, Data for Democracy is in a great position to inform the debate. We might get it wrong, and we'll definitely be told "that's not how you do it" -- but we'll be creative, try new things, and produce something useful in the process.
We'll collect data in May, and build models in June. The goal is to have a ranked list by the end of June.
For the time being, we're storing data on data.world.
Advice we've received that might be helpful:
Two reasons a seat might be vulnerable are 1) it has a lot of high-propensity moderates, 2) it has a high-concentraction of low-propensity voters of the power that isn't currently in power. It's important to understand what type of state/district you have. In scenario 1, the opposition campaign would be about persuading moderates, and in scenario 2, it's a "get out the vote" campaign.
Some states/districts (northeast for Ds, southeast for Rs), are unlikely to flip. Conventional wisdom says the best place to look is the midwest.
For now, join the #p-just-politics channel on Slack and ping @jonathon.