Birds of a Feather Do Flock Together

Abstract

Friends and spouses tend to be similar in a broad range of characteristics, such as age, educational level, race, religion, attitudes, and general intelligence. Surprisingly, little evidence has been found for similarity in personality—one of the most fundamental psychological constructs. We argue that the lack of evidence for personality similarity stems from the tendency of individuals to make personality judgments relative to a salient comparison group, rather than in absolute terms (i.e., the reference-group effect), when responding to the self-report and peer-report questionnaires commonly used in personality research. We employed two behavior-based personality measures to circumvent the reference-group effect. The results based on large samples provide evidence for personality similarity between romantic partners ( n = 1,101; rs = .20–.47) and between friends ( n = 46,483; rs = .12–.31). We discuss the practical and methodological implications of the findings.

Personality homophily affects male social bonding in wild Assamese macaques (Macaca assamensis)

“…Our result that individuals more similar in Connectedness form stronger social bonds supports the hypothesis of a shared evolutionary origin of personality homophily as partner choice strategy in human and non-human primates (Bahns et al, 2016; Massen & Koski, 2014). In humans the personality dimensions most closely matched in friends are extraversion and agreeableness (e.g., Blaz, 1983; Caspi et al, 2005; Dishion, Patterson, Stoolmiller, & Skinner, 1991; Ilmarinen, Vainikainen, Verkasalo, & Lönnqvist, 2017; Maaß, Lämmle, Bensch, & Ziegler, 2016; Markey & Kurtz, 2006; van Zalk & Denissen, 2015; Youyou et al, 2017), which partly resembles our findings. Aspects of the Connectedness trait, like proximity, social tolerance, and friendly approach, roughly correspond to the sociable or affiliative facets of extraversion associated with enjoyment of social interactions (Denissen & Penke, 2008).…”

“…Personality is defined as inter-individual differences in behaviour, affect and cognition that are relatively consistent across time and (Réale, Reader, Sol, McDougall, & Dingemanse, 2007). Personality homophily has been found in human spouses (e.g., Byrne, 1997; Klohnen & Luo, 2003; Youyou, Stillwell, Schwartz, & Kosinski, 2017) and improves reproductive success in monogamous rodents, birds, and fish (Ariyomo & Watt, 2013; Dingemanse, Both, Drent, & Tinbergen, 2004; Gabriel & Black, 2012; Rangassamy, Dalmas, Féron, Gouat, & Rödel, 2015; Schuett, Dall, & Royle, 2011). Similarity in certain personality traits is associated with the strength of social bonds in chimpanzees (Massen & Koski, 2014), higher-quality relationships in capuchin monkeys (Morton, Weiss, Buchanan-Smith, & Lee, 2015), relationship stability from one year to the next in juvenile rhesus macaques (Weinstein & Capitanio, 2012) and pairing-success of adult rhesus macaques in a laboratory setting (Capitanio, Blozis, Snarr, Steward, & McCowan, 2015).…”

Recreating the Relationship between Subjective Wellbeing and Personality Using Machine Learning: An Investigation into Facebook Online Behaviours

“…This may be attributed to the failure to recreate the variable in the first hypothesis. Based on the multiple regression analyses, openness to experience became positively correlated with SWB in the machine learning model, which could be attributed to reference group bias through the administration of the NEO-PI-R via Facebook [24,25]. A higher correlation was found between agreeableness and SWB, which is due to the unknowing use of identical digital behaviours to predict the variables or multicollinearity, which inflated the relationship.…”

“…This reduces reference group effect bias, typically found in self-report questionnaire measures (such as the IPIP; International Personality Item Pool), which refers to describing oneself in relation to others. Human activity monitored by digital services and devices allows behaviours to be digitally mediated, permitting large-scale samples to be obtained with the minimisation of sampling error and reduction of group effect bias [24,25]. Using the Internet as a research tool permits the collection of diverse samples and generally produces better quality data [1].…”

“…Studies have shown the ability to predict a person's personality at a superficial level using machine learning [2,3,23,25,26,28,41]; however, the relationship between machine learning predicted SWB and personality has not yet been explored. Kosinski, Stillwell and Graepel [3] found the test retest reliability of the openness to experience FFM trait to approximate the predicted versus observed correlation score, suggesting that the observation of user Facebook 'Likes' is about as informative as that from a personality questionnaire test score.…”