Personality and Politics - Myers-Briggs Personality Types on Twitter in the US 2016 Presidential Election

Sep 17, 2026

Twitter enables examination of public reactions at large scale, but interpreting discourse benefits from understanding the people behind it. This study uses Myers-Briggs Type Inventory (MBTI) categories to test whether supporters and detractors of US 2016 presidential candidates, Hillary Clinton and Donald Trump, differ in personality. MBTI types are inferred from tweet writing via the EthosIO system and large hashtag-based user-group samples. Statistical testing identifies extremely significant personality differences between Clinton and Trump supporters, while several other comparisons show no significant effect.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages2

Reading Time5 min

AccessFree to download

Introduction

Method: MBTI inference from Twitter

EthosIO system and data collection

Group definitions with political hashtags

Results: personality differences and statistical tests

Discussion: confounding factors

Personality and Politics: Myers-Briggs Personality Types on Twitter in the US 2016 Presidential Election Patrick Juola [juola@mathcs.duq.edu](juola@mathcs.duq.edu) Duquesne University, United States of America Sean Vinsick [sean.vinsick@gmail.com](sean.vinsick@gmail.com) Duquesne University, United States of America As a social media platform, Twitter (twitter.com) offers opportunities to examine public reactions in what could be described as the world's largest village square. Twitter provides an opportunity not only to participate in public discourse, but even to shape it. However, to fully understand this discourse, it is helpful to understand the people behind the discourse. Stylometric authorship profiling (Argamon, et al, 2009) provides an example of this. People are free to post their opinions, but by analyzing the writing style of the individual tweets, we can infer other attributes of the individual authors. In this study, we infer personality categories using the well-known Myers-Briggs Type Inventory (MBTI) to analyze whether or not there are any differences between the supporters (and detractors) of the major party candidates, Hillary Clinton (D) and Donald Trump (R) . The MBTI categorizes people along four major axes, as encoded in a four-character summary (for example, ENFJ: Extroverted, iNtuitive, Feeling, Judging) . We have shown (Gray and Juola, 2011; Juola et al., 2013) that personality can be inferred with high accuracy from writing, and further that MBTI personality types can be gleaned specifically from Twitter feeds. Using The EthosIO system developed by Juola & Associates (www.ethosio.com), we have applied this (Juola, Vinsick, and Ryan, 2016) to large-scale analyses of the demographics of personality on Twitter, finding substantial differences between the accepted distribution of personality in the general US population and between the distribution of personality among active Twitter participants. For example, introverts make up approximately 50% of the general US population, but nearly 80% of active Twitter users. Similarly, nearly 3/5 of the general US population are "sensing" (S) [as opposed to "intuitive" (N)], but half or fewer Twitter users are. Two specific subgroups, INFP and INFJ, are vastly overrepresented on Twitter, being only about 5% of the overall US population, but 30% or more of the samples gleaned from Twitter. We extend this to analyzing personality differences between politically disparate groups of Twitter participants. As with (Juola, Vinsick, and Ryan, 2016), we harvested a large group of user names from the Twitter sample feed, selecting users whose public tweets included one of several political hashtags. Based on the hashtags seen, we divided participants into four groups: anti-Clinton (identified by one or more of'\#NeverHillary', '\#CrookedHillary', '\#WhichHillary','\#DraftOurDaughters', '\#hillary4prison', '\#hillary4prison2016', '\#StopHillary', '\#CrimeWithHer', or'\#Killary'); pro-Clinton ('\#ImWithHer', '\#Clinton','\#ClintonKaine16', '\#ClintonKaine2016', '\#HillaryClinton'], '\#ClintonKaine', '\#WhyIWantHillary','\#HillarysArmy', or '\#Hillary2016'); anti-Trump ('\#NeverTrump', '\#dumptrump', '\#trumptaxreturns','\#dontvotefortrump', '\#dumpthetrump', '\#boycotttrump', '\#trumpsexism'); and pro-Trump ('\#ImWithYou', '\#TrumpTrain', '\#MakeAmericaGreatAgain', '\#TrumpPence16', '\#TrumpPence2016','\#Trump', '\#AltRight', '\#VoteTrump', '\#TeamTrump') This gave us approximately 600 user names for each of the four groups in our preliminary dataset. These user names were submitted to the EthosIO personality analyzer to produce distributional data for each subgroups. We therefore had in our preliminary corpus 651 pro-Clinton subjects, 587 pro-Trump subjects, 635 anti-Clinton subjects and 639 anti-Trump subjects, fora total of 2512 total user names, divided across 16 MBTI categories (details in full paper) . As expected from previous work, the overall s

FAQs

How does the study infer MBTI personality types from Twitter data?

It applies the EthosIO personality analyzer to tweets, using writing-style information to infer MBTI categories represented by four-letter summaries.

How were Twitter participants grouped for the analysis?

Participants were selected based on political hashtags and divided into four groups: anti-Clinton, pro-Clinton, anti-Trump, and pro-Trump, yielding roughly 600 user names per group in the preliminary dataset.

What statistical outcome does the study report when comparing Clinton and Trump supporters?

The study reports extremely significant differences in MBTI type distributions between Clinton supporters and Trump supporters, and also significant differences between groups labeled as Democrats versus Republicans.

Sep 17, 2026

Uploaded by Taylor Morgan