commitment, conscientiousness, costly signaling theory, equilibrium selection, emotion, empathy, ethics, evolutionary psychology, fitness indicators, genetic correlations, good genes, good parents, good partners, human courtship, kin selection, kindness, individual differences, intelligence, mate choice, mental health, moral virtues, mutation load, mutual choice, person perception, personality, reciprocal altruism, sexual fidelity, sexual selection, social cognition, virtue ethics “Human good turns out to be the activity of the soul exhibiting excellence.” Aristotle (350 BC) Moral evolution theories have emphasized kinship, reciprocity, group selection, and equilibrium selection. Yet, moral virtues are also sexually attractive. Darwin suggested that sexual attractiveness may explain many aspects of human morality. This paper updates his argument by integrating recent research on mate choice, person perception, individual differences, costly signaling, and virtue ethics. Many human virtues may have evolved in both sexes through mutual mate choice to advertise good genetic quality, parenting abilities, and/or partner traits. Such virtues may include kindness, fidelity, magnanimity, and heroism, as well as quasi-moral traits like conscientiousness, agreeableness, mental health, and intelligence. This theory leads to many testable predictions about the phenotypic features, genetic bases, and social-cognitive responses to human moral virtues. A

Abstract: This study measures risk attitudes using two paid experiments: the Holt and Laury (2002) procedure and a variation of the game show Deal or No Deal. The participants also completed a series of personality questionnaires developed in the psychology literature including the risk domains of Weber, Blais, and Betz (2002). As in previous studies risk attitudes vary within subjects across elicitation methods. However, this variation can be explained by individual personality traits. Specifically, subjects behave as though the Holt and Laury task is an investment decision while the Deal or No Deal task is a gambling decision.

which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background: Personality traits may form a part of the aetiology of opioid dependence. For instance, opioid dependence may result from self-medication in emotionally unstable individuals, or from experimenting with drugs in sensation seekers. The five factor model (FFM) has obtained a central position in contemporary personality trait theory. The five factors are: Neuroticism, Extraversion, Openness to Experience, Agreeableness and Conscientiousness. Few studies have examined whether there is a distinct personality pattern associated with opioid dependence. Methods: We compared FFM personality traits in 65 opioid dependent persons (mean age 27 years, 34 % females) in outpatient counselling after a minimum of 5 weeks in buprenorphine replacement therapy, with those in a non-clinical, age- and sex-matched sample selected from a national database. Personality traits were assessed by a Norwegian version of the Revised NEO Personality Inventory (NEO PI-R), a 240-item self-report questionnaire. Cohen's d effect sizes were calculated for the differences in personality trait scores. Results: The opioid-dependent sample scored higher on Neuroticism, lower on Extraversion and

Research article Personality disorders in substance abusers: Validation of the DIP-Q through principal components factor analysis and canonical correlation analysis

Social media is a place where users present themselves to the world, revealing personal details and insights into their lives. We are beginning to understand how some of this information can be utilized to improve the users ’ experiences with interfaces and with one another. In this paper, we are interested in the personality of users. Personality has been shown to be relevant to many types of interactions; it has been shown to be useful in predicting job satisfaction, professional and romantic relationship success, and even preference for different interfaces. Until now, to accurately guage users ’ personalities, they needed to take a personality test. This made it impractical to use personality analysis in many social media domains. In this paper, we present a method by which a user’s personality can be accurately predicted through the publicly available information on their Facebook profile. We will describe the type of data collected, our methods of analysis, and the machine learning techniques that allow us to successfully predict personality. We then discuss the implications this has for social media design, interface design, and broader domains.