Personality analysis has been widely studied in psychology, neuropsychology,
and signal processing fields, among others. From the past few years, it also
became an attractive research area in visual computing. From the computational
point of view, by far speech and text have been the most considered cues of
information for analyzing personality. However, recently there has been an
increasing interest from the computer vision community in analyzing personality
from visual data. Recent computer vision approaches are able to accurately
analyze human faces, body postures and behaviors, and use these information to
infer apparent personality traits. Because of the overwhelming research
interest in this topic, and of the potential impact that this sort of methods
could have in society, we present in this paper an up-to-date review of
existing vision-based approaches for apparent personality trait recognition. We
describe seminal and cutting edge works on the subject, discussing and
comparing their distinctive features and limitations. Future venues of research
in the field are identified and discussed. Furthermore, aspects on the
subjectivity in data labeling/evaluation, as well as current datasets and
challenges organized to push the research on the field are reviewed.

本篇论文系统总结了基于视觉计算的表观性格特征识别的现有方法，讨论比较了这些方法的独特特点和限制；同时也讨论了该领域未来的研究方向和数据标注 / 评估的主观性问题，还简要回顾了当前数据集和挑战。

第一印象：基于视觉的明显人格特征分析调查

First Impressions: A Survey on Vision-Based Apparent Personality Trait  Analysis

While social media has become an empowering agent to individual voices and
freedom of expression, it also facilitates anti-social behaviors including
online harassment, cyberbullying, and hate speech. In this paper, we present
the first comparative study of hate speech instigators and target users on
Twitter. Through a multi-step classification process, we curate a comprehensive
hate speech dataset capturing various types of hate. We study the distinctive
characteristics of hate instigators and targets in terms of their profile
self-presentation, activities, and online visibility. We find that hate
instigators target more popular and high profile Twitter users, and that
participating in hate speech can result in greater online visibility. We
conduct a personality analysis of hate instigators and targets and show that
both groups have eccentric personality facets that differ from the general
Twitter population. Our results advance the state of the art of understanding
online hate speech engagement.

本文通过对 Twitter 上仇恨言论发起人和目标用户进行多步分类研究，发现仇恨发起人的目标是较受欢迎和高知名度的 Twitter 用户，参与仇恨言论会导致更大的在线可见性，并通过个性分析表明，这两个群体具有与一般 Twitter 人口不同的离心性格面貌。