In 2012, we found that Facebook “likes” and “PTAT” metrics, when added to a model including standard forecasting fundamentals, can produce surprisingly accurate vote forecasts of campaigns for the U.S. Senate. The question remains, however, whether our results in 2012 were an anomaly or a tool to expand the statistical forecasting of election results to campaigns for Congress.
With that important caveat lurking in the back of our minds, we have carefully captured and analyzed Facebook metrics from the pages of candidates running for U.S. Senate since September 2013. We have taken this data and added it into a simple model, what we call the Facebook Forecasting Model, to arrive at predictions of the percent – in a two-way race – each candidate will earn on Election Day in November. Now, with most of the primaries behind us (except Alaska and New Hampshire!), we are ready to begin publishing a weekly update of our forecast.
The forecast is presented as two-week and three-week, rolling averages of the model’s predictions. From 2012, we found that averaging the predictions over these time periods produced forecasts with a higher R-Square.
This week, we start with eight Senate races. We will add several more, including Minnesota, Alaska, and New Hampshire, before all is said and done.
How accurate will our forecasts be? Only time will tell. We have confidence in the model and in our ability to track Facebook metrics accurately. But the real proof will be “in the pudding” that comes out of the blast chiller on the night of November 4th.