First impressions: A survey on vision-based apparent personality trait analysis

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.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.Peer ReviewedPostprint (author's final draft

Emotional Creativity: A Meta-analysis and Integrative Review

Emotional creativity (EC) is a pattern of cognitive abilities and personality traits related to originality and appropriateness in emotional experience. EC has been found to be related to various constructs across different fields of psychology during the past 30 years, but a comprehensive examination of previous research is still lacking. The goal of this review is to explore the reliability of use of the Emotional Creativity Inventory (ECI) across studies, to test gender differences and to compare levels of EC in different countries. Thirty-five empirical studies focused on EC were retrieved and the coefficients required for the meta-analysis extracted. The meta-analysis revealed that women showed significantly higher EC than men (total N = 3,555). The same gender differences were also found when testing scores from three ECI subscales, i.e. emotional novelty, emotional preparedness and emotional effectiveness/authenticity. When comparing EC in 10 different countries (total N = 4,375), several cross-cultural differences were revealed. The Chinese sample showed a significantly lower average ECI total score than all the other countries. Based on the integration of results, the avenues for future research on EC and the breadth of influence of the concept of EC across different fields of psychology are discussed. Keywords: Emotional Creativity, Review, Meta-Analyses, Meta-Analysis, Definition, Emotional Creativity Inventory, ECI, Reliability, Gender Differences, Cross-cultural, Cross-culture, Personality Traits, NEO Personality Inventory, Big Five, Extraversion, Agreeableness, Openness to Experience, Introversion, Neuroticism, Emotions, Creativity, Cognition, Cognitive Abilities, Affect, Fantasy, Coping, Alexithymia, Anhedonia, Self-understanding, Motivation, Creativeness, Innovative Performance, Creative Ability, Artistic Creativity, Creative Thinking. MeSH Headings: Emotions, Creativity, Affect, Affective Symptoms, Gender, Sex, Gender Identity, Cross-Cultural Comparison, Transcultural Studies, Temperament, Extraversion, Neuroticism, Anhedonia, Creativeness, Cognition, Cognitive Function, Artistic Creativity, Creative Ability, Creative Thinkin

Personality in Computational Advertising: A Benchmark

In the last decade, new ways of shopping online have increased the possibility of buying products and services more easily and faster than ever. In this new context, personality is a key determinant in the decision making of the consumer when shopping. A person’s buying choices are influenced by psychological factors like impulsiveness; indeed some consumers may be more susceptible to making impulse purchases than others. Since affective metadata are more closely related to the user’s experience than generic parameters, accurate predictions reveal important aspects of user’s attitudes, social life, including attitude of others and social identity. This work proposes a highly innovative research that uses a personality perspective to determine the unique associations among the consumer’s buying tendency and advert recommendations. In fact, the lack of a publicly available benchmark for computational advertising do not allow both the exploration of this intriguing research direction and the evaluation of recent algorithms. We present the ADS Dataset, a publicly available benchmark consisting of 300 real advertisements (i.e., Rich Media Ads, Image Ads, Text Ads) rated by 120 unacquainted individuals, enriched with Big-Five users’ personality factors and 1,200 personal users’ pictures

Analysing and using subjective criteria to improve dental care recommendation systems

Online reviews and rating sites are shaping industries as the users rely on recommendations given by former consumers and sharing opinions on the web. Dentistry has also been impacted by dental patients' reviews. This paper classifies trust-related information for dental care recommendations onto 4 categories: context, relationship, reputation and subjective criteria. It discusses each category and describes how they help focussing on trust when matching patients and dentists in brief. The paper then focuses on subjective criteria and presents the results of a survey aimed at showing trustrelated information emerged from subjective characteristics. Traits of personalities are used as subjective characteristics of patients and that of dentists are derived from the online patients' reviews. 580 Australian patients were surveyed to determine what factors affect their decision to find the trusted dentist. Subjective characteristics of dentists such as dentists' qualities and experienced dentists are considered the most important factors after location and cost. The most preferred dentists' qualities by almost all types of personalities are experienced, professional and quality of service. When the patients are further classified based on levels of fear, their preferences for dentists' qualities changed. Subjective qualities of both patients and dentists are important factors to improve the matching capability for the dental care recommendation systems

How does money influence health?

This study looks at hundreds of theories to consider how income influences health. There is a graded association between money and health – increased income equates to better health. But the reasons are debated.<p></p> Researchers have reviewed theories from 272 wide-ranging papers, most of which examined the complex interactions between people’s income and their health throughout their lives.<p></p> Key points<p></p> This research identifies four main ways money affects people’s wellbeing:<p></p> Material: Money buys goods and services that improve health. The more money families have, the better the goods they can buy.<p></p> Psychosocial: Managing on a low income is stressful. Comparing oneself to others and feeling at the bottom of the social ladder can be distressing, which can lead to biochemical changes in the body, eventually causing ill health.<p></p> Behavioural: For various reasons, people on low incomes are more likely to adopt unhealthy behaviours – smoking and drinking, for example – while those on higher incomes are more able to afford healthier lifestyles.<p></p> Reverse causation (poor health leads to low income): Health may affect income by preventing people from taking paid employment. Childhood health may also affect educational outcomes, limiting job opportunities and potential earnings

Enabling the Analysis of Personality Aspects in Recommender Systems

Existing Recommender Systems mainly focus on exploiting users’ feedback, e.g., ratings, and reviews on common items to detect similar users. Thus, they might fail when there are no common items of interest among users. We call this problem the Data Sparsity With no Feedback on Common Items (DSW-n-FCI). Personality-based recommender systems have shown a great success to identify similar users based on their personality types. However, there are only a few personality-based recommender systems in the literature which either discover personality explicitly through filling a questionnaire that is a tedious task, or neglect the impact of users’ personal interests and level of knowledge, as a key factor to increase recommendations’ acceptance. Differently, we identifying users’ personality type implicitly with no burden on users and incorporate it along with users’ personal interests and their level of knowledge. Experimental results on a real-world dataset demonstrate the effectiveness of our model, especially in DSW-n-FCI situations

Personalised trails and learner profiling within e-learning environments

This deliverable focuses on personalisation and personalised trails. We begin by introducing and defining the concepts of personalisation and personalised trails. Personalisation requires that a user profile be stored, and so we assess currently available standard profile schemas and discuss the requirements for a profile to support personalised learning. We then review techniques for providing personalisation and some systems that implement these techniques, and discuss some of the issues around evaluating personalisation systems. We look especially at the use of learning and cognitive styles to support personalised learning, and also consider personalisation in the field of mobile learning, which has a slightly different take on the subject, and in commercially available systems, where personalisation support is found to currently be only at quite a low level. We conclude with a summary of the lessons to be learned from our review of personalisation and personalised trails

Investigating the physiological underpinnings of proactive and reactive behavioural types in grey seals (Halichoerus grypus): Trial deployment of a minimally invasive data logger for recording heart rate and heart rate variability in a wild free-ranging breeding pinniped species

Individuals differ non-randomly in their responses to stressors, exhibiting consistent individual differences (CIDs) in behavioural and physiological coping mechanisms commonly referred to as coping styles. Grey seals (Halichoerus grypus) are one of the few mammal species in which CIDs in stress responses have been documented in wild populations, though evidence thus far has been purely behavioural. Physiologically, coping styles can be distinguished by differences in the autonomic regulation of cardiac activity, which can be measured using heart rate variability (HRV). The objectives of this study were two-fold. First, to assess the suitability of Polar® RS800CX monitors and H2/H3 sensors for conducting HRV analyses in grey seals. Second, to quantify inter-individual variation, repeatability, and reproductive performance correlates of baseline HRV. Polar® devices were deployed successfully during the 2013 breeding season on female grey seals (N = 15) on the Isle of May, Scotland, and were capable of recording HR patterns that characterise phocid seals at rest on land. However, artefacts were widespread and biased HRV metrics. Filtration and correction protocols were able to counteract the effects of artefacts, but severely limited the amount of data available for analysis. There were significant inter-individual differences in baseline HRV, which could not be explained by factors associated with the breeding season (e.g. percentage mass loss, day of lactation), diurnal rhythms (e.g. time of day), or stressors (e.g. days since capture). These differences in baseline HRV showed consistency across early and late lactation. Individuals appeared to separate into two groups: those with consistently lower or higher baseline HRV, characteristic of proactive and reactive coping styles, respectively. Furthermore, females with lower baseline HRV showed greater maternal transfer efficiency – though there were no associations between baseline HRV and maternal expenditure (i.e. maternal mass loss, kgday–1) or fitness outcomes (i.e. pup mass gain, kgday–1). These findings build upon previous studies on behavioural CIDs in female grey seals by providing the first preliminary evidence for physiological CIDs that are associated with maternal investment. However, due to small sample sizes, further studies are required to determine whether these findings are truly indicative of coping styles. In their current form, the use of Polar® devices requires several caveats and further studies are needed to fully realise their potential. Future research should focus on validation against simultaneously recorded ECGs to improve artefact detection and correction, and modification to minimise the occurrence of artefacts. Despite their limitations, Polar® devices have immense potential as a minimally invasive research tool for conducting HRV analyses in the field