TY - GEN
T1 - Do First Impressions Influence Elections? A Computational Study of Voter Perceptions in Simulated Peruvian Elections (2023)
AU - Aybar-Flores, Alejandro
AU - Maehara, Rocío
AU - Benites, Luis
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
PY - 2026
Y1 - 2026
N2 - The study evaluates the influence of presidential candidates’ personality traits on voting intentions, addressing a notable gap in political behavior research. Given Peru’s political institutions’ historical instability and fragmentation, understanding how voting operates in this context is relevant. The objective of the study is to examine the relationship between candidates’ personality traits and voter preferences using computer vision and deep learning techniques. The methodology involves using deep learning models to estimate the Big Five personality traits from video data of candidates during a simulated electoral process. The analysis utilizes two primary datasets: the First Impressions V2, containing labeled personality trait ratings to train the models, and a manually constructed database of Peruvian and international presidential candidates’ videos to determine personality traits from the trained models. Subsequently, surveys are conducted to track voting intentions in a simulated electoral process. The findings demonstrate significant correlations between specific personality traits, such as extraversion and agreeableness, and voting patterns, showing that personality traits can affect voter decisions, offering a more profound comprehension of voter decision-making processes and political dynamics to enhance communication strategies, evaluate political positions, and maintain party cohesion.
AB - The study evaluates the influence of presidential candidates’ personality traits on voting intentions, addressing a notable gap in political behavior research. Given Peru’s political institutions’ historical instability and fragmentation, understanding how voting operates in this context is relevant. The objective of the study is to examine the relationship between candidates’ personality traits and voter preferences using computer vision and deep learning techniques. The methodology involves using deep learning models to estimate the Big Five personality traits from video data of candidates during a simulated electoral process. The analysis utilizes two primary datasets: the First Impressions V2, containing labeled personality trait ratings to train the models, and a manually constructed database of Peruvian and international presidential candidates’ videos to determine personality traits from the trained models. Subsequently, surveys are conducted to track voting intentions in a simulated electoral process. The findings demonstrate significant correlations between specific personality traits, such as extraversion and agreeableness, and voting patterns, showing that personality traits can affect voter decisions, offering a more profound comprehension of voter decision-making processes and political dynamics to enhance communication strategies, evaluate political positions, and maintain party cohesion.
KW - Computer Vision
KW - Deep Learning
KW - Personality Traits
KW - Peru
KW - Voting Intentions
UR - https://www.scopus.com/pages/publications/105021841496
U2 - 10.1007/978-3-032-04581-2_22
DO - 10.1007/978-3-032-04581-2_22
M3 - Conference contribution
AN - SCOPUS:105021841496
SN - 9783032045805
T3 - Lecture Notes in Networks and Systems
SP - 307
EP - 326
BT - Software Engineering
A2 - Silhavy, Radek
A2 - Silhavy, Petr
PB - Springer Science and Business Media Deutschland GmbH
T2 - 14th Computer Science On-line Conference, CSOC 2025
Y2 - 1 April 2025 through 3 April 2025
ER -