Senate races as close as 0.5% based on news and social buzz…


As you know these Senate races are highly publicized and close in the polls:

Elizabeth Warren v. Scott Brown (MA) +4.7 RCP / +4.9 538 Blog

Chris Murphy v. Linda McMahon (CT) +3.1 RCP / +4.6 538 Blog

Jeff Flake v. Richard Carmona (AZ) +0.6 RCP / +2.9 538 Blog

Richard Mourdock v. Joe Donnelly (IN) +5 RCP / +1.8 538 Blog

Sherrod Brown v. Josh Mandel (OH) +5.2 RCP / +6.4 538 Blog

Here’s what TrendPo Rank has them today:

Elizabeth Warren v. Scott Brown (MA)  TR-5 to TR-14 | 0.5% difference

Linda McMahon v. Chris Murphy (CT)    TR-216 to TR-225 | 0.5% difference

Jeff Flake v. Richard Carmona (AZ)       TR-173 to TR-177 | 0.2% difference

Richard Mourdock v. Joe Donnelly (IN)  TR-21 to TR-152 | 8% difference *

Sherrod Brown v. Josh Mandel (OH)      TR-164 to TR-175 | 0.6% difference

The TrendPo Rank calculates every politician relative to all 1600 ballot candidates for Nov. 6th (Governors, Senators, House incumbents and challengers).

So the fact that two candidates are as little as eleven or even three (ex: Flake v. Carmona) TrendPo Ranks apart shows how closely their news and social is tied together. But we definitely didn’t expect these Senate races to be as close as 0.3% out of 1600 national politicians.

We’ll continue to analyze this data and show our findings here in the blog.

 

(previously we showed this as 0.8%, but the race in Indiana is TR-21 to TR-152, an 8% difference between Mourdock and Donnelly)

About TrendPo Rank: Each day TrendPo scrapes various sorts of social media, national media, beltway media, and state media to track buzz among national politicians. We run sentiment analysis on the tone of every news article — eg. sentiment analysis against content, not message; and we track gains and losses on every politician’s social pages. From all this Big Data, we calculate a daily rank of trending “buzz”. We call this the TrendPo Rank.

TrendPo Rank is an indicator of news and social buzz. Time will tell if this type of buzz actually correlates to election results but in the meantime, we think it’s an interesting data point in understanding the political message cycle:

Politicians PUSH message to news outlets who INTERPRET the message to mass audiences who VET the message using social media as their voice.

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