As we reach the close of the data gathering phase of this research project, day t-7 saw the Clinton-Trump primary activity levels reach an all time high for division at Clinton x70. Historically, high levels of conversation such as this are bad for a candidate, although in 2015 they were very good for Trump. Something to consider, I am juxtaposing #ImWithHer to #Trump2016.

What do I think is happening? Without social network analysis and other approaches I don’t have a definitive answer. My guess is that the comparative evaluation phase of the process is over and that people are taking one, last, hard look at Clinton. Since this point, Trump activity has been rising and Clinton activity may be starting to normalize.

In terms of timing and election modeling, what does this mean? First, early voting is well underway in many states, so connecting anything related to polls with exit polls with actual results is fishy at this point. Second, For horse-race style analysis, this makes the election much less fun as exit polls are better than normal polls. Oregon for example is largely finished voting, if I vote at this point I will need to take my ballot to an official drop site. Third, even without running Cohen’s D on the daily twitter returns, I can tell you that Comey’s letter had a dramatic effect on Twitter traffic. Trump activity decreased to campaign record lows while Clinton surged to campaign highs.

Overall, I am reminded of the problems with producing social facts. Alain Desrosières The Politics of Large Numbers (a must read for computational critical/cultural studies) calls for a consideration of the categories and processes in statistical analysis. In social network analysis we tend to consider the census of a data set rather than a sample. It is nice to know that we have an inflection point to study and that we can understand the entire dynamic system around it, but it is discomforting to know that it can be enacted so quickly.