# Automated Inference on Sociopsychological Impressions of Attractive Female Faces

arXiv: https://arxiv.org/abs/1612.04158 · HTML: https://mlsanity.com/paper/1612.04158/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Dec 2016.

## Built on by (most cited first, 1 of 1)

- [Measuring Trustworthiness or Automating Physiognomy? A Comment on Safra, Chevallier, Gr`ezes, and Baumard (2020)](https://mlsanity.com/paper/2202.08674/) (2022)

## Abstract (arXiv)

This article is a sequel to our earlier work [25]. The main objective of our research is to explore the potential of supervised machine learning in face-induced social computing and cognition, riding on the momentum of much heralded successes of face processing, analysis and recognition on the tasks of biometric-based identification. We present a case study of automated statistical inference on sociopsychological perceptions of female faces controlled for race, attractiveness, age and nationality. Our empirical evidences point to the possibility of training machine learning algorithms, using example face images characterized by internet users, to predict perceptions of personality traits and demeanors.