10:21 PM EDT
10:21 PM EDT

    TLDR;
Q: Why was there such a large bump in the number of Hillary and Trump
followers at 10:21 PM EDT during the second Presidential Debate?
A: I’m not sure, but maybe it has something to do with abortion or
marriage equality?

During the last two presidential debates MITH has been collecting Twitter data
using the words trump and hillary. Neil Fraistat’s motivation for
organizing our Night Against
Hate this week was to identify social media accounts for hate groups
that are in the Southern Poverty Law Center’s Extremist
Files, and then use this information to help see how these groups
were using Trump’s own words in their tweets. So it was super to see How
Trump Took Hate Groups Mainstream in Mother Jones just yesterday.
Sarah Posner and David Neiwert have been on this trail for a while, and
their write up is a must read.
We’re still talking about what we want to look for in the debate
datasets and how we want to use the spreadsheet
that we collaboratively built. Look for another blog post about the
Night Against Hate soon.
One limitation of looking for patterns in collected Twitter data is
that the Presidential Debates are high volume events. We know that the
Twitter streaming API only gives us a portion of all the available
tweets when there is a spike in traffic. For example our dataset for the
first
debate contains 1,303,084 tweets that mentioned “hillary” and the
Twitter API let us know that at least 730,512 tweets were not delivered.
Very little is known about what kind of sample Twitter provides, and
without the full picture it is difficult to draw inferences from the
numbers.
followers_count
But one interesting metric that is available is the number of
followers a person has. This number can be particularly interesting to
look at over time as it rises and falls. Every tweet that you get from
the Twitter API includes a User Object which
in turn contains the followers_count for that user at the time
that the request was made of the Twitter API. So if you collect data in
real time from the Twitter Streaming
API you get a moving picture of a user’s followers. What’s also
super handy is that in every retweet you get the user object
for the retweeter, and also for the user who sent the original
tweet.
During the debates you can count on many people retweeting the
candidates tweets. This means you can get smooth record of how many
followers they have by the minute … or even second. The fact that you’re
not getting all the tweets at a given point in time doesn’t
really matter.
So I wrote a very simple utility that reads through Twitter data I
collected with twarc looking
for particular users and collects how many followers they have at
particular times and writes it out as a CSV file, for analysis in a
spreadsheet:



New Followers
I thought it could be interesting to look at the number of new
followers each candidate received during the first debate. In
theory these would be “people” that had decided to follow Clinton or
Trump on Twitter as they were watching the debate. I put people
in scare quotes there because it is possible, and perhaps even likely,
that there are bot armies creating these accounts. You’d have to track
who these new accounts were and sample them to know for sure.
So with that caveat in mind here’s what the graph for the first
debate looked like:

It was encouraging (for me) to see that Hillary was gaining more
followers than Trump during the debate. There were a few interesting
changes in the graph, but I was mostly distracted by the fact that
Hillary was outpacing Trump so much in new followers. We collected data
for the second
debate so I decided to look again with the same code:

I was pleased to see Clinton is gaining more supporters than Trump
again; but this graph looks noticeably different. Do you see the bump in
followers at 10:21 PM EDT (02:21 GMT). What happened there? Well, thanks
to the Web you can see exactly what happened there: it was the question
from Beth Miller about the Supreme Court that begins at 10:19:54:




If you watch the time tick by you can see in the exact minute of
10:21 PM Hillary is saying this:

I want a Supreme Court that will stick with Roe v. Wade and a woman’s
right to choose, and I want a Supreme Court that will stick with
marriage equality. Now, Donald has put forth the names of some people
that he would consider. And among the ones that he has suggested are
people who would reverse Roe v. Wade and reverse marriage equality. I
think that would be a terrible mistake and would take us backwards.

What is truly bizarre is that there is a bump at that point for both
candidates. Maybe this points at a problem in my code, or my spreadsheet
data (I’m happy to share the Tweet ID datasets if you would like to
look for yourself). Or perhaps the bump is part of some kind of backlog
in Twitter’s infrastructure? Maybe there’s a bot army that’s working for
both candidates? It would be necessary to inspect the users to get a
sense of that.
But maybe, just maybe, this data points at the fact that a Woman’s
right to choose and marriage equality are still polarizing and hot
button issues, more so than any others, for folks in this years
election? At least for folks who use Twitter…which is definitely not all
voters. That’s probably the biggest caveat there is.
If you have ideas, questions, criticisms about any of this I’d love
to hear from you.

Updates



(edsu?) (peteskomoroch?)
fascinating. I'd love to see what the rate of new followers looks like -
seems like Trump's bump is slightly bigger?

— Jane Wang ((janexwang?)) October
16, 2016



I’m not sure my rate of change calculation was the best. I simply
subtracted the new subscribers in the previous minute from new
subscribers in the current minute. It does show that Trump got a bigger
bump in this minute, and really highlights how much of a change it was.
If you have an idea for calculating the rate of change that is better
take a look at the data.


  