If they Google You, Do you Win?

In a way, this election is a referendum on “do actions speak louder than words”, is what people do in the privacy of their internet browsing more reflective of their future behavior than what they tell pollsters? And while I have focused on twitter as a barometer of public opinion, there are other data sources that could signal the private thoughts and future actions of voters. The linked NYT article, “If they Google you, Do you Win?”, mentions using the Google queries “Trump Clinton” vs. “Clinton Trump” as signals of voter interest, with the respective queries reflecting bias towards the candidate listed first, i.e. “Clinton Trump” would reflect bias towards Clinton. Using this methodology, I researched Google trends for Battleground states to see where public opinion may be. The data are displayed below.


For the month of October 2016, “Trump Clinton” leads “Clinton Trump” in every state with the exception of Nevada.

You might say Trump is a polarizing celebrity, and for that reason he may be top of mind even if the individual plans to vote for Clinton. Okay, well then let’s penalize Trump 10%. Even in that case, ‘Factored “Trump Clinton”‘ indicates that, with the exception of Nevada, the three states that are in play are Virginia, Iowa, and Florida.

So while it is unclear in which direction the election will result, I believe we may be surprised at how close the results turn out to be, and that one thing we may remember is the discrepancy between what was reported in the polls leading up to the election and what actually happened online. We only have 4 days left to see which source provides a clearer signal of truth, and until then….Good luck to both candidates!

Gauging US Politics with Reddit

Reddit is an entertainment, social networking, and news site where registered users can vote submissions up or down in a bulletin board-like fashion . Content entries are organized by areas of interest called “subreddits.” This post uses subreddits /r/Republican and /r/Democrats to analyze US Politics as of July 22, 2015.

Thanks to Dr. Randal Olson and his reddit-analysis script, we crawled /r/Republican and /r/Democrats. Making word clouds, we visualize word frequency, largest to smallest by count.




redditdemocratswordcloudThe word clouds provide a high level view of the subreddits. Now let’s dive in to gain insight!

/r/Republican has 16,942 readers, and /r/Democrats has 15,152.

During the timespan 6/22/15 – 7/22/15, 86,609 words appeared in /r/Republican and 73,156 words appeared in /r/Democrats. We will compare word frequency as % of total. In the event of significant difference, the greater of the two will be bolded.

/r/Republican % of total /r/Democrats % of total
“Good” 0.11 0.20
“Bad” 0.06 0.10
 /r/Republican % of total  /r/Democrats % of total
“Love” 0.05 0.05
“Hate” 0.05 0.05
 /r/Republican % of total   /r/Democrats % of total
“GOP” 0.07 0.27
“Fox” 0.02 0.08
 /r/Republican % of total  /r/Democrats % of total
“Trump” 0.30 0.15
“Hillary” 0.07 0.28
  /r/Republican % of total  /r/Democrats % of total
“Obama” 0.12 0.18
“Bush” 0.07 0.13
 /r/Republican % of total  /r/Democrats % of total
“Country” 0.11 0.14
“States” 0.14 0.07
 /r/Republican % of total  /r/Democrats % of total
“Students” 0.04 0.00
“School” 0.04 0.02
 /r/Republican % of total  /r/Democrats % of total
“Gay” 0.06 0.09
“Marriage” 0.10 0.13
 /r/Republican % of total  /r/Democrats % of total
“Inequality” 0.01 0.02
“Equality” 0.00 0.03
 /r/Republican % of total  /r/Democrats % of total
“White” 0.06 0.10
“Black” 0.04 0.04
 /r/Republican % of total  /r/Democrats % of total
“Health” 0.02 0.10
“Insurance” 0.03 0.05
 /r/Republican % of total  /r/Democrats % of total
“Workers” 0.02 0.04
“Unions” 0.05 0.01
 /r/Republican % of total  /r/Democrats % of total
“Gun” 0.05 0.04
“Control” 0.03 0.10
 /r/Republican % of total  /r/Democrats % of total
“Minimum” 0.02 0.06
“Wage” 0.02 0.08
 /r/Republican % of total  /r/Democrats % of total
“Church” 0.06 0.01
“Religion” 0.01 0.01

While we’ll let you come to your own conclusions, here are the insights we found surprising:

  • Greater Frequency of “GOP” and “Fox” in /r/Democrats
  • Greater Frequency of “Students” in /r/Republicans
  • Greater Frequency of “White” in /r/Democrats
  • Greater Frequency of “Union” in /r/Republicans

That’s it for now. Please comment with additional insights or reach out directly at: