10.2 Presidential Social Intelligence Battleground Tracker — Post Debate Top Issues and Sentiment
A pulse of how potential voters in battleground states are discussing the Presidential candidates
Please read the background post on this project if it is your first time reading.
Past posts:
— Our initial dataset from the week of 7.3 was detailed here.
— Data from the week of 7.11 was detailed here
— Data from the week of 7.19 was detailed here.
— Aggregate data to date through 8.14 was detailed here
— Language data from the weeks of 8.07 & 8.14 was detailed here
— Aggregate data through 8.25 was detailed here.
— Language data from 8.21–8.28 was detailed here
— Language data from 8.28–9.04 was detailed here
— Aggregate data through 9.5 was detailed here
— Language data from 9.04–9.11 was detailed here
— Aggregate daily support gained/lost data through 9.17 was detailed here
— A first look at Supreme Court Data was detailed here
— A deeper dive into Supreme Court Data was detailed here
— A language comparison between voters in NC and FL was detailed here
— An overview of the pre-debate top issues was detailed here
— Aggregate daily support gained/lost data through 9.30 was detailed here
Battleground States in our Analysis: AZ, CO, FL, IA, ME, MI, MN, NV, NH, NC, PA, TX, WI
Date Source: All data is publicly available and anonymized for our analysis from Twitter, Facebook, Online Blogs, & Message Boards.
Technology Partners: Eyesover & Relative Insight
Post Debate Top Issues and Sentiment
Before the debate (and before this morning's news about POTUS and COVID) we tracked the top issues dominating the discussion around each candidate.
A post debate look proves how “warp speed” today’s news cycle and social conversations moves. Not to mention these numbers through yesterday are now completely moot at the time of this posting.
Prior to the debate, the Supreme Court vacancy dominated the conversation — that quickly moved into issues around Taxation based on the New York Times story on Trump’s taxes.
Coming out of the debate Racial Issues, the Alt-Right, and COVID rocketed back to the top of the discussion.
Now, as of this post, COVID is no doubt going to move back to the top for the foreseeable future, based on the news of POTUS and FLOTUS postive test results.
Here is a state-by-state look at issues and sentiment post debate.
Arizona:
Colorado:
Florida:
Iowa:
Maine:
Michigan:
Minnesota:
North Carolina:
New Hampshire:
Nevada:
Pennsylvania:
Texas:
Wisconsin:
Support Gain/Lost Overview
The “Support Gain/Lost” metric is built by analyzing the language used in social posts about the presidential candidates. As battleground voters use language to indicate support for a candidate, our systems register “+1” in “Support Gained” for that date. A post expressing negative support is registered as “-1” in “Support Lost.”
These numbers are based on holistic expressions of support gained/lost, or shifts to neutral, from a unique social account. Only shifts in categorization are registered per social account after an initial signal is measured. (EX: a post from someone supporting Trump is not counted two days in a row.)
There are 6 metrics we monitor on a daily basis across each state:
— Previous Non-Supporter to Neutral: (a post indicating a previous non-supporter has moved to a more neutral stance on a candidate)
— Suport Gained: (a post indicating support gained for Trump or Biden)
— Support Lost: (a post indicating support lost for Trump or Biden)
— Previous Supporter to Neutral: (a post indicating a previous supporter has moved to a more neutral stance on a candidate)
— Net Daily Gain/Lost: (the daily net of Support Gained v. Support Lost)
— Net Daily Neutral Shift: (the daily net of “Shifts to Neutral”)
Language Analysis
Building off the “Support Gained v. Lost” classification, we are aggregating an anonymized dataset of social posts that represent support for each candidate. This dataset allows us to compare and analyze the language used by “Biden Supporters” v. “Trump Supporters.”
From this analysis, we can better understand the issues/topics/trends that cause voters to express support or opposition toward a candidate. It also exposes overall patterns from the language used between the two supporter datasets.
— The analysis is processed via the Relative Insight language comparison platform.
The chart below shows the current size of the language data set:
About The Author
Adam Meldrum is an award-winning political & digital strategist. He is the Founder/President of the Republican media-buying operation AdVictory LLC, a Senior Advisor at DDC Public Affairs, and a Senior Advisor at WinRed. Adam serves on The Board of Directors at HeadCount, a non-partisan organization that uses the power of music to register voters and promote participation in democracy.
Since 2006 Adam has produced award-winning work for and advised campaigns/organizations such as; Governor Rick Snyder, Governor Bruce Rauner, Governor Doug Burgum, Governor Bill Lee, Ambassador Ron Weiser, Senator Ben Sasse, Senator John McCain, Senator Rand Paul, The Republican National Committee and the U.S. Chamber of Commerce.
Adam’s work on the forefront of technology, data, and analytics was featured by OZY Media in a profile: “Meet the GOP’s Chatbot and Artificial Intelligence Guru”. He is a die-hard Michigan State University fan/alumni and pretty obsessed with Phish and The Grateful Dead. He resides in Washington D.C. with his beautiful wife Christina and their weird puppy, Basil.
Personal Website: http://www.adammeldrum.me/
