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.

screen-shot-2016-11-03-at-5-49-10-pm

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!

Hillary: Age Perception Problem?

“I come from the ‘60s, a long time ago,” Hillary Clinton said at Saturday’s Democratic Presidential debate, in response to a question about student activism. The gaffe has mostly fallen on deaf ears.

Hillary Clinton is 68 years old. She was born October 26, 1947. Here is a visualization showing the age distribution of US Presidents upon assuming the Oval Office.

Screen Shot 2015-11-19 at 12.53.10 PM (2)

To date, only three US Presidents between the ages 65-69 have assumed the Oval Office. Once again, Hillary Clinton is 68 years old. She “come(s) from the ‘60s, a long time ago.”

Granted, the US population is aging. However, when selecting Presidents, this aging US population has trended towards younger Presidents.

Age upon assuming Oval Office: Barack Obama, 47 years old; George W. Bush, 54 years old; Bill Clinton, 46 years old.

Hillary wishes to dispel the age perception. HFA recently posted the SnapChat logo wearing a most recognizable pantsuit.

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Of all the social networks, Snapchat skews youngest. According to Business Insider, 45% of Snapchat users are between the ages 18-24.Screen Shot 2015-11-19 at 12.44.44 PM (2)

Thus, a strategy has emerged: capture the young mind. Win the unspoiled voter, who is excited by the prospect of casting her first vote. Btw, Hillary uses Snapchat.

Further evidence of the strategy:

Twitter Banner displaying young prospective voters

Screen Shot 2015-11-19 at 12.53.58 PM (2)

HFA blog post appealing to youth and “a new age”

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We should expect age to become a louder issue as the campaigns unfold. For reference, here are the ages of all the candidates, both Democrats and Republicans. Those between the ages 44- 60 are in bold.

Hilary Clinton, 68 years old

Bernie Sanders, 74 yeards old

Martin O’Malley, 52 years old

Donald Trump, 69 years old

Ben Carson, 64 years old

Marco Rubio, 44 years old

Ted Cruz, 44 years old

Jeb Bush, 62 years old

Carly Fiorina, 61 years old

John Kasich, 63 years old

Rand Paul, 52 years old

Twitter – US Presidential Campaigns, Nov 7, 2015: Heat Map

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This heat map visualizes the US Presidential Campaigns on Twitter as of November 7, 2015. Darkest blue indicates the highest value. Grey indicates the lowest value.

Takeaways:

  • Bernie Sanders receives the most engagement per Tweet
  • Donald Trump Tweets the most of any candidate
  • Donald Trump and Hillary Clinton have the most Followers
  • Hillary Clinton, Ben Carson, Jeb Bush, and Chris Christie have curated new Twitter feeds for the 2016 election, as indicated by low Total Tweets
  • With the exception of Donald Trump, the Democrats rank highest across the board, indicating digital competency
  • With the exception of Carly Fiorina, all candidates Tweet a moderate amount per day

Moral Foundations: Reddit Political Communities

Moral Foundations Theory is a social psychological theory intended to explain the origins of and variation in human moral reasoning. The theory proposes moral foundations such as fairness, care, in-group, authority, and purity, and has been popularized by psychologist Jonathan Haidt in his book The Righteous Mind.

Haidt describes human morality as it relates to politics and proposes differences between conservatives and liberals as they relate to the moral foundations (TED Talk). Specifically, whereas conservatives appeal to fairness, care, in-group, authority, and purity equally, liberals appeal to fairness and care more than they appeal to in-group, authority, and purity.

Setting out to observe this phenomenon within Reddit Political Communities, I performed word frequency analyses on the /r/Republican and /r/Democrats corpora, totaling the words for each moral foundation, as defined by the LIWC dictionary. Comparing the totals, I found a trend consistent with Moral Foundations Theory. The visualization shows the moral foundations for /r/Democrats normalized against those for /r/Republican, with each value for /r/Republican set at 100%.

reddit_moralfoundations

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.

/r/Republican

redditrepublicanwordcloud

/r/Democrats

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:

andrewshamlet@gmail.com