scholarly journals How Are Personality States Associated with Smartphone Data?

2020 ◽  
Vol 34 (5) ◽  
pp. 687-713
Author(s):  
Dominik Rüegger ◽  
Mirjam Stieger ◽  
Marcia Nißen ◽  
Mathias Allemand ◽  
Elgar Fleisch ◽  
...  
Keyword(s):  
Big Five ◽  
Ambient Noise ◽  
Psychological Research ◽  
Big Five Personality ◽  
Data Set ◽  
Personality Psychology ◽  
Smartphone Sensors ◽  
Self Assessments ◽  
Day Of The Week ◽  
State Responses

Smartphones promise great potential for personality science to study people's everyday life behaviours. Even though personality psychologists have become increasingly interested in the study of personality states, associations between smartphone data and personality states have not yet been investigated. This study provides a first step towards understanding how smartphones may be used for behavioural assessment of personality states. We explored the relationships between Big Five personality states and data from smartphone sensors and usage logs. On the basis of the existing literature, we first compiled a set of behavioural and situational indicators, which are potentially related to personality states. We then applied them on an experience sampling data set containing 5748 personality state responses that are self–assessments of 30 minutes timeframes and corresponding smartphone data. We used machine learning analyses to investigate the predictability of personality states from the set of indicators. The results showed that only for extraversion, smartphone data (specifically, ambient noise level) were informative beyond what could be predicted based on time and day of the week alone. The results point to continuing challenges in realizing the potential of smartphone data for psychological research. © 2020 The Authors. European Journal of Personality published by John Wiley & Sons Ltd on behalf of European Association of Personality Psychology

scholarly journals Can Facebook likes predict the purchase probability of electricity storage systems?

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Stefan Poier
Keyword(s):  
Personality Traits ◽  
Big Five ◽  
Control Sample ◽  
Big Five Personality Traits ◽  
Photovoltaic System ◽  
Big Five Personality ◽  
Personality Psychology ◽  
Electricity Storage ◽  
Combining Data ◽  
User Groups

AbstractThis study among owners of photovoltaic systems investigates whether users' Big Five personality traits derived from their Facebook likes contribute to whether or not they adopt an electricity storage. It is based on the finding that the digital footprint, especially the Facebook likes, can in part predict the personality of users better than friends and family. The survey was conducted among 159 Facebook users in Germany who owned a photovoltaic system. For comparison, a control sample with data from the German Socio-Economic Panel with 425 photovoltaic owners among 7286 individuals was used. The results show that, for extraversion, agreeableness, and neuroticism, the mean scores could be sufficiently predicted. However, a positive correlation could only be detected for extraversion. The comparison of the user groups could not provide satisfying results. None of the Big Five personality traits could be used to distinguish the two user groups from each other. Although the results did not support the hypotheses, this study offers insights into the possibilities of combining data mining, personality psychology, and consumer research.

scholarly journals Loneliness and the Big Five Personality Traits: A Meta–Analysis

2020 ◽  
Vol 34 (1) ◽  
pp. 8-28 ◽  
Author(s):  
Susanne Buecker ◽  
Marlies Maes ◽  
Jaap J. A. Denissen ◽  
Maike Luhmann
Keyword(s):  
Personality Traits ◽  
Big Five ◽  
Structural Equation ◽  
Variance Estimation ◽  
Meta Analysis ◽  
The Other ◽  
Personality Factors ◽  
Big Five Personality ◽  
Personality Psychology ◽  
Total N

This preregistered meta–analysis ( k = 113, total n = 93 668) addressed how the Big Five dimensions of personality (extraversion, agreeableness, conscientiousness, neuroticism, and openness) are related to loneliness. Robust variance estimation accounting for the dependency of effect sizes was used to compute meta–analytic bivariate correlations between loneliness and personality. Extraversion ( r = −.370), agreeableness ( r = −.243), conscientiousness ( r = −.202), and openness ( r = −.107) were negatively related to loneliness. Neuroticism ( r = .358) was positively related to loneliness. These associations differed meaningfully in strength depending on how loneliness was assessed. Additionally, meta–analytic structural equation modelling was used to investigate the unique association between each personality trait and loneliness while controlling for the other four personality traits. All personality traits except openness remained statistically significantly associated with loneliness when controlling for the other personality traits. Our results show the importance of stable personality factors in explaining individual differences in loneliness. © 2020 European Association of Personality Psychology

‘Personality in its Natural Habitat’ Revisited: A Pooled, Multi–sample Examination of the Relationships between the Big Five Personality Traits and Daily Behaviour and Language Use

2020 ◽  
Vol 34 (5) ◽  
pp. 753-776 ◽  
Author(s):  
Allison M. Tackman ◽  
Erica N. Baranski ◽  
Alexander F. Danvers ◽  
David A. Sbarra ◽  
Charles L. Raison ◽  
...  
Keyword(s):  
Big Five ◽  
Language Use ◽  
Natural Habitat ◽  
Past Research ◽  
Assessment Method ◽  
Big Five Personality ◽  
Personality Psychology ◽  
Pooled Data ◽  
Small College ◽  
Gender Specific

Past research using the Electronically Activated Recorder (EAR), an observational ambulatory assessment method for the real–world measurement of daily behaviour, has identified several behavioural manifestations of the Big Five domains in a small college sample ( N = 96). With the use of a larger and more diverse sample of pooled data from N = 462 participants from a total of four community samples who wore the EAR from 2 to 6 days, the primary purpose of the present study was to obtain more precise and generalizable effect estimates of the Big Five–behaviour relationships and to re–examine the degree to which these relationships are gender specific. In an extension of the original article, the secondary purpose of the present study was to examine if the Big Five–behaviour relationships differed across two facets of each Big Five domain. Overall, while several of the behavioural manifestations of the Big Five were generally consistent with the trait definitions (replicating some findings from the original article), we found little evidence of gender differences (not replicating a basic finding from the original article). Unique to the present study, the Big Five–behaviour relationships were not always comparable across the two facets of each Big Five domain. © 2020 European Association of Personality Psychology

scholarly journals Indicators of Affect Dynamics: Structure, Reliability, and Personality Correlates

2020 ◽  
Vol 34 (6) ◽  
pp. 1060-1072 ◽  
Author(s):  
Leon P. Wendt ◽  
Aidan G.C. Wright ◽  
Paul A. Pilkonis ◽  
William C. Woods ◽  
Jaap J.A. Denissen ◽  
...  
Keyword(s):  
Personality Traits ◽  
Big Five ◽  
High Reliability ◽  
Big Five Personality Traits ◽  
Big Five Personality ◽  
Personality Psychology ◽  
Total N ◽  
Structure Reliability ◽  
Complex Indicators ◽  
Affect Dynamics

Researchers are increasingly interested in the affect dynamics of individuals for describing and explaining personality and psychopathology. Recently, the incremental validity of more complex indicators of affect dynamics (IADs; e.g. autoregression) has been called into question (Dejonckheere et al., 2019), with evidence accumulating that these might convey little unique information beyond mean level and general variability of emotions. Our study extends the evidence for the construct validity of IADs by investigating their redundancy and uniqueness, split–half reliability based on indices from odd–numbered and even–numbered days, and association with big five personality traits. We used three diverse samples that assessed daily and momentary emotions, including community participants, individuals with personality pathology, and their significant others (total N = 1192, total number of occasions = 51 278). Mean and variability of affects had high reliability and distinct nomological patterns to big five personality traits. In contrast, more complex IADs exhibited substantial redundancies with mean level and general variability of emotions. When partialing out these redundancies by using residual variables, some of the more complex IADs had acceptable reliability, but only a few of these showed incremental associations with big five personality traits, indicating that IADs have limited validity using the current assessment practices. © 2020 The Authors. European Journal of Personality published by John Wiley & Sons Ltd on behalf of European Association of Personality Psychology

Tracking Fluctuations in Psychological States using Social Media Language: A Case Study of Weekly Emotion

2020 ◽  
Vol 34 (5) ◽  
pp. 845-858
Author(s):  
Johannes C. Eichstaedt ◽  
Aaron C. Weidman
Keyword(s):  
Big Data ◽  
Big Five ◽  
Emotional Valence ◽  
Data Set ◽  
Personality Psychology ◽  
Aggregated Data ◽  
Psychological States ◽  
Final Data ◽  
Valence And Arousal

Personality psychologists are increasingly documenting dynamic, within–person processes. Big data methodologies can augment this endeavour by allowing for the collection of naturalistic and personality–relevant digital traces from online environments. Whereas big data methods have primarily been used to catalogue static personality dimensions, here we present a case study in how they can be used to track dynamic fluctuations in psychological states. We apply a text–based, machine learning prediction model to Facebook status updates to compute weekly trajectories of emotional valence and arousal. We train this model on 2895 human–annotated Facebook statuses and apply the resulting model to 303 575 Facebook statuses posted by 640 US Facebook users who had previously self–reported their Big Five traits, yielding an average of 28 weekly estimates per user. We examine the correlations between model–predicted emotion and self–reported personality, providing a test of the robustness of these links when using weekly aggregated data, rather than momentary data as in prior work. We further present dynamic visualizations of weekly valence and arousal for every user, while making the final data set of 17 937 weeks openly available. We discuss the strengths and drawbacks of this method in the context of personality psychology's evolution into a dynamic science. © 2020 European Association of Personality Psychology

scholarly journals Longitudinal Associations between Delinquent Behaviour of Friends and Delinquent Behaviour of Adolescents: Moderation by Adolescent Personality Traits

2015 ◽  
Vol 29 (4) ◽  
pp. 468-477 ◽  
Author(s):  
Meike Slagt ◽  
Judith Semon Dubas ◽  
Maja Deković ◽  
Gerbert J. T. Haselager ◽  
Marcel A. G. van Aken
Keyword(s):  
Personality Traits ◽  
Big Five ◽  
Protective Factor ◽  
Rank Order ◽  
Big Five Personality ◽  
Adolescent Delinquency ◽  
Personality Psychology ◽  
Delinquent Behaviour ◽  
Best Friends ◽  
Longitudinal Associations

In this longitudinal study, we examined whether personality traits (parent–rated Big Five personality traits) render some adolescents more susceptible than others to delinquent behaviour of friends, predicting rank–order changes in adolescents‘ self–reported delinquent behaviour. We examine susceptibility to both perceived (reported by adolescents) and self–reported (reported by friends) delinquent behaviour of friends. Participants in this two–wave study were 285 Dutch adolescents and their best friends. The adolescents (50% girls) were 15.5 years old on average (SD = 0.8 years), and their best friends (N = 176; 58% girls) were 15.1 years old (SD = 1.5 years). Perceived (but not self–reported) delinquency of friends predicted a stronger increase in adolescent delinquency 1 year later, especially among adolescents low or average on conscientiousness. Emotional stability, agreeableness, extraversion and openness did not moderate associations between delinquency of friends and delinquency of adolescents. Our findings show that low conscientiousness serves as a risk factor, increasing vulnerability to perceived delinquent behaviour of friends, while high conscientiousness serves as a protective factor, increasing resilience to perceived delinquent behaviour of friends. Our findings also show that adolescents are susceptible to, and differ in susceptibility to, friends‘ delinquent behaviour as they perceive it—not to delinquent behaviour as reported by friends themselves. Copyright © 2015 European Association of Personality Psychology

scholarly journals Successful Explanations Start with Accurate Descriptions: Questionnaire Items as Personality Markers for More Accurate Predictions

2018 ◽  
Vol 32 (3) ◽  
pp. 186-201 ◽  
Author(s):  
Anne Seeboth ◽  
René Mõttus
Keyword(s):  
Big Five ◽  
European Association ◽  
Predictive Power ◽  
Penalized Regression ◽  
Big Five Personality ◽  
Personality Psychology ◽  
National Child Development Study ◽  
Large Numbers ◽  
Behavioural Specificity ◽  
Per Se

Personality–outcome associations, typically represented using the Big Five personality domains, are ubiquitous, but often weak and possibly driven by the constituents of these domains. We hypothesized that representing the associations using personality questionnaire items (as markers for personality nuances) could increase prediction strength. Using the National Child Development Study ( N = 8719), we predicted 40 diverse outcomes from both the Big Five domains and their 50 items. Models were trained (using penalized regression) and applied for prediction in independent sample partitions (with 100 permutations). Item models tended to out–predict Big Five models (explaining on average 30% more variance), regardless of outcomes’ independently rated breadth versus behavioural specificity. Moreover, the predictive power of Big Five domains per se was at least partly inflated by the unique variance of their constituent items, especially for generally more predictable outcomes. Removing the Big Five variance from items marginally reduced their predictive power. These findings are consistent with the possibility that the associations of personality with outcomes often pertain to (potentially large numbers of) specific behavioural, cognitive, affective, and motivational characteristics represented by single questionnaire items rather than to the broader (underlying) traits that these items are ostensibly indicators of. This may also have implications for personality–based interventions. Copyright © 2018 European Association of Personality Psychology

College Student Samples Are Not Always Equivalent: The Magnitude of Personality Differences across Colleges and Universities

2016 ◽  
Author(s):  
Katherine S. Corker ◽  
Brent Donnellan ◽  
Su Yeong Kim ◽  
Seth J. Schwartz ◽  
Byron Zamboanga
Keyword(s):  
Big Five ◽  
Psychological Research ◽  
Colleges And Universities ◽  
Group Differences ◽  
Big Five Personality ◽  
Post Secondary ◽  
Individual Level ◽  
Personality Differences ◽  
Cultural Research ◽  
Level Information

Objective: This research examined the magnitude of personality differences across different colleges and universities to understand (1) how much students at different colleges vary from one another and (2) whether there are site level variables that can explain observed differences.Method: Nearly 8,600 students at 30 colleges and universities completed a Big Five personality trait measure. Site level information was obtained from the Integrated Post-Secondary Education System database (U.S.Department of Education).Results: Multi-level models revealed that each of the Big Five traits showed significant between-site variability, even after accounting for individual level demographic differences. Some site-level variables (e.g., enrollment size, requiring letters of recommendation) explained between-site differences in traits, but many tests were not statisticallysignificant.Conclusions: Student samples at different universities differed in terms of average levels of Big Five personality domains. This raises the possibility that personality differences may explain differences in research results obtained when studying students at different colleges and universities. Furthermore, results suggest that research that compares findings for only a few sites (e.g., much cross cultural research) runs the risk of overgeneralizing differences between specific samples to broader group differences. These results underscore the value of multisite collaborative research efforts to enhance psychological research.

scholarly journals Model "Big Five" personality and criminal behavior

2013 ◽  
Vol 6 (1) ◽  
pp. 102-109
Author(s):  
David Sánchez-Teruel ◽  
Mª Auxiliadora Robles-Bello
Keyword(s):  
Big Five ◽  
Criminal Behavior ◽  
Future Research ◽  
Big Five Personality ◽  
Assessment Instruments ◽  
Field Of Study ◽  
Personality Psychology ◽  
Theoretical Issues

It reflect on the theoretical issues that currently versa Personality Psychology in general and antisocial or criminal behavior in particular. It discusses how the model can be used personality "Big Five" applied to the field of crime, and shows the variables that the literature presented as more predictive, through one of the most widely used assessment instruments at present. It currently advises finding, meeting points between the various existing theories, for that personality does not become a field of study restricted exclusively to researchers and scholars. It discuss the most important results in the application of the "Big Five" personality of the offender, and posess some limitations, as future research for practitioners and researchers.

Deeply Confusing: Conflating Difficulty With Deep Revelation on Personality Assessment

2018 ◽  
Vol 10 (4) ◽  
pp. 514-521 ◽  
Author(s):  
Randy Stein ◽  
Alexander B. Swan
Keyword(s):  
Big Five ◽  
Personality Assessment ◽  
Direct Method ◽  
Personality Type ◽  
Personality Inventory ◽  
Big Five Personality ◽  
Personality Assessments ◽  
Personality Psychology ◽  
Moderating Factors

The factors that contribute to lay expectations of personality assessments are not well understood. Five studies demonstrate that people conflate difficulty of personality assessment items with revelations of deep insights. As a result, popular yet invalid assessments of personality can be seen as “deeper” than assessments from social and personality psychology. In Study 1, participants evaluated items from a popular personality “type” assessment as more difficult and better at revealing deep insights into personality than Big-Five personality inventory items. Studies 2 and 3 replicate this effect experimentally using a manipulation of assessment items’ difficulty. Studies 4 and 5 show that the same effect also holds for a less direct method of supposed personality assessment (e.g., assessments that ask about which colors are associated with trivial concepts). Moderating factors and the popularity of shoddy personality assessments are discussed.

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