Michal Kosinski

All Publications

• Evaluating large language models in theory of mind tasks. Proceedings of the National Academy of Sciences of the United States of America Kosinski, M. 2024; 121 (45): e2405460121

  Abstract

  Eleven large language models (LLMs) were assessed using 40 bespoke false-belief tasks, considered a gold standard in testing theory of mind (ToM) in humans. Each task included a false-belief scenario, three closely matched true-belief control scenarios, and the reversed versions of all four. An LLM had to solve all eight scenarios to solve a single task. Older models solved no tasks; Generative Pre-trained Transformer (GPT)-3-davinci-003 (from November 2022) and ChatGPT-3.5-turbo (from March 2023) solved 20% of the tasks; ChatGPT-4 (from June 2023) solved 75% of the tasks, matching the performance of 6-y-old children observed in past studies. We explore the potential interpretation of these results, including the intriguing possibility that ToM-like ability, previously considered unique to humans, may have emerged as an unintended by-product of LLMs' improving language skills. Regardless of how we interpret these outcomes, they signify the advent of more powerful and socially skilled AI-with profound positive and negative implications.

  View details for DOI 10.1073/pnas.2405460121

  View details for PubMedID 39471222

• Facial recognition technology and human raters can predict political orientation from images of expressionless faces even when controlling for demographics and self-presentation. The American psychologist Kosinski, M., Khambatta, P., Wang, Y. 2024

  Abstract

  Carefully standardized facial images of 591 participants were taken in the laboratory while controlling for self-presentation, facial expression, head orientation, and image properties. They were presented to human raters and a facial recognition algorithm: both humans (r = .21) and the algorithm (r = .22) could predict participants' scores on a political orientation scale (Cronbach's α = .94) decorrelated with age, gender, and ethnicity. These effects are on par with how well job interviews predict job success, or alcohol drives aggressiveness. The algorithm's predictive accuracy was even higher (r = .31) when it leveraged information on participants' age, gender, and ethnicity. Moreover, the associations between facial appearance and political orientation seem to generalize beyond our sample: The predictive model derived from standardized images (while controlling for age, gender, and ethnicity) could predict political orientation (r ≈ .13) from naturalistic images of 3,401 politicians from the United States, the United Kingdom, and Canada. The analysis of facial features associated with political orientation revealed that conservatives tended to have larger lower faces. The predictability of political orientation from standardized images has critical implications for privacy, the regulation of facial recognition technology, and understanding the origins and consequences of political orientation. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

  View details for DOI 10.1037/amp0001295

  View details for PubMedID 38512164

• Human-like intuitive behavior and reasoning biases emerged in large language models but disappeared in ChatGPT. Nature computational science Hagendorff, T., Fabi, S., Kosinski, M. 2023; 3 (10): 833-838

  Abstract

  We design a battery of semantic illusions and cognitive reflection tests, aimed to elicit intuitive yet erroneous responses. We administer these tasks, traditionally used to study reasoning and decision-making in humans, to OpenAI's generative pre-trained transformer model family. The results show that as the models expand in size and linguistic proficiency they increasingly display human-like intuitive system 1 thinking and associated cognitive errors. This pattern shifts notably with the introduction of ChatGPT models, which tend to respond correctly, avoiding the traps embedded in the tasks. Both ChatGPT-3.5 and 4 utilize the input-output context window to engage in chain-of-thought reasoning, reminiscent of how people use notepads to support their system 2 thinking. Yet, they remain accurate even when prevented from engaging in chain-of-thought reasoning, indicating that their system-1-like next-word generation processes are more accurate than those of older models. Our findings highlight the value of applying psychological methodologies to study large language models, as this can uncover previously undetected emergent characteristics.

  View details for DOI 10.1038/s43588-023-00527-x

  View details for PubMedID 38177754

• Facial recognition technology can expose political orientation from naturalistic facial images. Scientific reports Kosinski, M. 2021; 11 (1): 100

  Abstract

  Ubiquitous facial recognition technology can expose individuals' political orientation, as faces of liberals and conservatives consistently differ. A facial recognition algorithm was applied to naturalistic images of 1,085,795 individuals to predict their political orientation by comparing their similarity to faces of liberal and conservative others. Political orientation was correctly classified in 72% of liberal-conservative face pairs, remarkably better than chance (50%), human accuracy (55%), or one afforded by a 100-item personality questionnaire (66%). Accuracy was similar across countries (the U.S., Canada, and the UK), environments (Facebook and dating websites), and when comparing faces across samples. Accuracy remained high (69%) even when controlling for age, gender, and ethnicity. Given the widespread use of facial recognition, our findings have critical implications for the protection of privacy and civil liberties.

  View details for DOI 10.1038/s41598-020-79310-1

  View details for PubMedID 33431957

• Deep Neural Networks Are More Accurate Than Humans at Detecting Sexual Orientation From Facial Images JOURNAL OF PERSONALITY AND SOCIAL PSYCHOLOGY Wang, Y., Kosinski, M. 2018; 114 (2): 246–57

  Abstract

  We show that faces contain much more information about sexual orientation than can be perceived or interpreted by the human brain. We used deep neural networks to extract features from 35,326 facial images. These features were entered into a logistic regression aimed at classifying sexual orientation. Given a single facial image, a classifier could correctly distinguish between gay and heterosexual men in 81% of cases, and in 71% of cases for women. Human judges achieved much lower accuracy: 61% for men and 54% for women. The accuracy of the algorithm increased to 91% and 83%, respectively, given five facial images per person. Facial features employed by the classifier included both fixed (e.g., nose shape) and transient facial features (e.g., grooming style). Consistent with the prenatal hormone theory of sexual orientation, gay men and women tended to have gender-atypical facial morphology, expression, and grooming styles. Prediction models aimed at gender alone allowed for detecting gay males with 57% accuracy and gay females with 58% accuracy. Those findings advance our understanding of the origins of sexual orientation and the limits of human perception. Additionally, given that companies and governments are increasingly using computer vision algorithms to detect people's intimate traits, our findings expose a threat to the privacy and safety of gay men and women. (PsycINFO Database Record

  View details for PubMedID 29389215

• Facial Width-to-Height Ratio Does Not Predict Self-Reported Behavioral Tendencies. Psychological science Kosinski, M. 2017; 28 (11): 1675-1682

  Abstract

  A growing number of studies have linked facial width-to-height ratio (fWHR) with various antisocial or violent behavioral tendencies. However, those studies have predominantly been laboratory based and low powered. This work reexamined the links between fWHR and behavioral tendencies in a large sample of 137,163 participants. Behavioral tendencies were measured using 55 well-established psychometric scales, including self-report scales measuring intelligence, domains and facets of the five-factor model of personality, impulsiveness, sense of fairness, sensational interests, self-monitoring, impression management, and satisfaction with life. The findings revealed that fWHR is not substantially linked with any of these self-reported measures of behavioral tendencies, calling into question whether the links between fWHR and behavior generalize beyond the small samples and specific experimental settings that have been used in past fWHR research.

  View details for DOI 10.1177/0956797617716929

  View details for PubMedID 28976810

• Birds of a Feather Do Flock Together: Behavior-Based Personality-Assessment Method Reveals Personality Similarity Among Couples and Friends PSYCHOLOGICAL SCIENCE Wu Youyou, Y. Y., Stillwell, D., Schwartz, H. A., Kosinski, M. 2017; 28 (3): 276-284

  View details for DOI 10.1177/0956797616678187

  View details for Web of Science ID 000396750500002

• Mining Big Data to Extract Patterns and Predict Real-Life Outcomes PSYCHOLOGICAL METHODS Kosinski, M., Wang, Y., Lakkaraju, H., Leskovec, J. 2016; 21 (4): 493-506

  Abstract

  This article aims to introduce the reader to essential tools that can be used to obtain insights and build predictive models using large data sets. Recent user proliferation in the digital environment has led to the emergence of large samples containing a wealth of traces of human behaviors, communication, and social interactions. Such samples offer the opportunity to greatly improve our understanding of individuals, groups, and societies, but their analysis presents unique methodological challenges. In this tutorial, we discuss potential sources of such data and explain how to efficiently store them. Then, we introduce two methods that are often employed to extract patterns and reduce the dimensionality of large data sets: singular value decomposition and latent Dirichlet allocation. Finally, we demonstrate how to use dimensions or clusters extracted from data to build predictive models in a cross-validated way. The text is accompanied by examples of R code and a sample data set, allowing the reader to practice the methods discussed here. A companion website (http://dataminingtutorial.com) provides additional learning resources. (PsycINFO Database Record

  View details for DOI 10.1037/met0000105

  View details for Web of Science ID 000393202300004

  View details for PubMedID 27918179

• Facebook as a Research Tool for the Social Sciences Opportunities, Challenges, Ethical Considerations, and Practical Guidelines AMERICAN PSYCHOLOGIST Kosinski, M., Matz, S. C., Gosling, S. D., Popov, V., Stillwell, D. 2015; 70 (6): 543-556

  Abstract

  Facebook is rapidly gaining recognition as a powerful research tool for the social sciences. It constitutes a large and diverse pool of participants, who can be selectively recruited for both online and offline studies. Additionally, it facilitates data collection by storing detailed records of its users' demographic profiles, social interactions, and behaviors. With participants' consent, these data can be recorded retrospectively in a convenient, accurate, and inexpensive way. Based on our experience in designing, implementing, and maintaining multiple Facebook-based psychological studies that attracted over 10 million participants, we demonstrate how to recruit participants using Facebook, incentivize them effectively, and maximize their engagement. We also outline the most important opportunities and challenges associated with using Facebook for research, provide several practical guidelines on how to successfully implement studies on Facebook, and finally, discuss ethical considerations. (PsycINFO Database Record

  View details for DOI 10.1037/a0039210

  View details for PubMedID 26348336

• Computer-based personality judgments are more accurate than those made by humans. Proceedings of the National Academy of Sciences of the United States of America Youyou, W., Kosinski, M., Stillwell, D. 2015; 112 (4): 1036-1040

  Abstract

  Judging others' personalities is an essential skill in successful social living, as personality is a key driver behind people's interactions, behaviors, and emotions. Although accurate personality judgments stem from social-cognitive skills, developments in machine learning show that computer models can also make valid judgments. This study compares the accuracy of human and computer-based personality judgments, using a sample of 86,220 volunteers who completed a 100-item personality questionnaire. We show that (i) computer predictions based on a generic digital footprint (Facebook Likes) are more accurate (r = 0.56) than those made by the participants' Facebook friends using a personality questionnaire (r = 0.49); (ii) computer models show higher interjudge agreement; and (iii) computer personality judgments have higher external validity when predicting life outcomes such as substance use, political attitudes, and physical health; for some outcomes, they even outperform the self-rated personality scores. Computers outpacing humans in personality judgment presents significant opportunities and challenges in the areas of psychological assessment, marketing, and privacy.

  View details for DOI 10.1073/pnas.1418680112

  View details for PubMedID 25583507

  View details for PubMedCentralID PMC4313801

• Large language models and humans converge in judging public figures' personalities. PNAS nexus Cao, X., Kosinski, M. 2024; 3 (10): pgae418

  Abstract

  ChatGPT-4 and 600 human raters evaluated 226 public figures' personalities using the Ten-Item Personality Inventory. The correlation between ChatGPT-4 and aggregate human ratings ranged from r = 0.76 to 0.87, outperforming the models specifically trained to make such predictions. Notably, the model was not provided with any training data or feedback on its performance. We discuss the potential explanations and practical implications of ChatGPT-4's ability to mimic human responses accurately.

  View details for DOI 10.1093/pnasnexus/pgae418

  View details for PubMedID 39359393

• Large language models know how the personality of public figures is perceived by the general public. Scientific reports Cao, X., Kosinski, M. 2024; 14 (1): 6735

  Abstract

  We show that people's perceptions of public figures' personalities can be accurately predicted from their names' location in GPT-3's semantic space. We collected Big Five personality perceptions of 226 public figures from 600 human raters. Cross-validated linear regression was used to predict human perceptions from public figures' name embeddings extracted from GPT-3. The models' accuracy ranged from r = .78 to .88 without controls and from r = .53 to .70 when controlling for public figures' likability and demographics, after correcting for attenuation. Prediction models showed high face validity as revealed by the personality-descriptive adjectives occupying their extremes. Our findings reveal that GPT-3 word embeddings capture signals pertaining to individual differences and intimate traits.

  View details for DOI 10.1038/s41598-024-57271-z

  View details for PubMedID 38509191

  View details for PubMedCentralID 4313801

• Political Attitudes and Disease Threat: Regional Pathogen Stress Is Associated With Conservative Ideology Only for Older Individuals. Personality & social psychology bulletin Brown, G. D., Walasek, L., Mullett, T. L., Quispe-Torreblanca, E. G., Fincher, C. L., Kosinski, M., Stillwell, D. 2023: 1461672231183199

  Abstract

  What environmental factors are associated with individual differences in political ideology, and do such associations change over time? We examine whether reductions in pathogen prevalence in U.S. states over the past 60 years are associated with reduced associations between parasite stress and conservatism. We report a positive association between infection levels and conservative ideology in the United States during the 1960s and 1970s. However, this correlation reduces from the 1980s onwards. These results suggest that the ecological influence of infectious diseases may be larger for older people who grew up (or whose parents grew up) during earlier time periods. We test this hypothesis by analyzing the political affiliation of 45,000 Facebook users, and find a positive association between self-reported political affiliation and regional pathogen stress for older (>40 years) but not younger individuals. It is concluded that the influence of environmental pathogen stress on ideology may have reduced over time.

  View details for DOI 10.1177/01461672231183199

  View details for PubMedID 37424438

• Overlap in meaning is a stronger predictor of semantic activation in GPT-3 than in humans. Scientific reports Digutsch, J., Kosinski, M. 2023; 13 (1): 5035

  Abstract

  Modern large language models generate texts that are virtually indistinguishable from those written by humans and achieve near-human performance in comprehension and reasoning tests. Yet, their complexity makes it difficult to explain and predict their functioning. We examined a state-of-the-art language model (GPT-3) using lexical decision tasks widely used to study the structure of semantic memory in humans. The results of four analyses showed that GPT-3's patterns of semantic activation are broadly similar to those observed in humans, showing significantly higher semantic activation in related (e.g., "lime-lemon") word pairs than in other-related (e.g., "sour-lemon") or unrelated (e.g., "tourist-lemon") word pairs. However, there are also significant differences between GPT-3 and humans. GPT-3's semantic activation is better predicted by similarity in words' meaning (i.e., semantic similarity) rather than their co-occurrence in the language (i.e., associative similarity). This suggests that GPT-3's semantic network is organized around word meaning rather than their co-occurrence in text.

  View details for DOI 10.1038/s41598-023-32248-6

  View details for PubMedID 36977744

  View details for PubMedCentralID 5863044

• Regional personality assessment through social media language. Journal of personality Giorgi, S., Nguyen, K. L., Eichstaedt, J. C., Kern, M. L., Yaden, D. B., Kosinski, M., Seligman, M. E., Ungar, L. H., Andrew Schwartz, H., Park, G. 2021

  Abstract

  OBJECTIVE: We explore the personality of counties as assessed through linguistic patterns on social media. Such studies were previously limited by the cost and feasibility of large-scale surveys; however, language-based computational models applied to large social media datasets now allow for large-scale personality assessment.METHOD: We applied a language-based assessment of the five factor model of personality to 6,064,267 U.S. Twitter users. We aggregated the Twitter-based personality scores to 2,041 counties and compared to political, economic, social, and health outcomes measured through surveys and by government agencies.RESULTS: There was significant personality variation across counties. Openness to experience was higher on the coasts, conscientiousness was uniformly spread, extraversion was higher in southern states, agreeableness was higher in western states, and emotional stability was highest in the south. Across 13 outcomes, language-based personality estimates replicated patterns that have been observed in individual-level and geographic studies. This includes higher Republican vote share in less agreeable counties and increased life satisfaction in more conscientious counties.CONCLUSIONS: Results suggest that regions vary in their personality and that these differences can be studied through computational linguistic analysis of social media. Furthermore, these methods may be used to explore other psychological constructs across geographies.

  View details for DOI 10.1111/jopy.12674

  View details for PubMedID 34536229

• Spouses' faces are similar but do not become more similar with time. Scientific reports Tea-Makorn, P. P., Kosinski, M. 2020; 10 (1): 17001

  Abstract

  The widely disseminated convergence in physical appearance hypothesis posits that long-term partners' facial appearance converges with time due to their shared environment, emotional mimicry, and synchronized activities. Although plausible, this hypothesis is incompatible with empirical findings pertaining to a wide range of other traits-such as personality, intelligence, attitudes, values, and well-being-in which partners show initial similarity but do not converge over time. We solve this conundrum by reexamining this hypothesis using the facial images of 517 couples taken at the beginning of their marriages and 20 to 69years later. Using two independent methods of estimating their facial similarity (human judgment and a facial recognition algorithm), we show that while spouses' faces tend to be similar at the beginning of marriage, they do not converge over time, bringing facial appearance in line with other personal characteristics.

  View details for DOI 10.1038/s41598-020-73971-8

  View details for PubMedID 33046769

• Individual-Level Analyses of the Impact of Parasite Stress on Personality: Reduced Openness Only for Older Individuals. Personality & social psychology bulletin Mullett, T. L., Brown, G. D., Fincher, C. L., Kosinski, M., Stillwell, D. 2019: 146167219843918

  Abstract

  The parasite stress hypothesis predicts that individuals living in regions with higher infectious disease rates will show lower openness, agreeableness, and extraversion, but higher conscientiousness. This article, using data from more than 250,000 U.S. Facebook users, reports tests of these predictions at the level of both U.S. states and individuals and evaluates criticisms of previous findings. State-level results for agreeableness and conscientiousness are consistent with previously reported cross-national findings, but others (a significant positive correlation with extraversion and no correlation with openness) are not. However, effects of parasite stress on conscientiousness and agreeableness are not found when analyses account for the data's hierarchical structure and include controls. We find that only openness is robustly related to parasite stress in these analyses, and we also find a significant interaction with age: Older, but not younger, inhabitants of areas of high parasite stress show lower openness. Interpretations of the findings are discussed.

  View details for DOI 10.1177/0146167219843918

  View details for PubMedID 31046588

• Privacy in the age of psychological targeting. Current opinion in psychology Matz, S. C., Appel, R. E., Kosinski, M. n. 2019; 31: 116–21

  Abstract

  Psychological targeting describes the practice of extracting people's psychological profiles from their digital footprints (e.g. their Facebook Likes, Tweets or credit card records) in order to influence their attitudes, emotions or behaviors through psychologically informed interventions at scale. We discuss how the increasingly blurred lines between public and private information, and the continuation of the outdated practices of notice and consent, challenge traditional conceptualizations of privacy in the context of psychological targeting. Drawing on the theory of contextual integrity, we argue that it is time to rethink privacy and move beyond the questions of who collects what data to how the data are being used. Finally, we suggest that regulations of psychological targeting should be accompanied by a mindset that fosters (1) privacy by design to make it easy for individuals to act in line with their privacy goals, as well as (2) disclosure by choice, to allow individuals to freely decide whether and when they might be willing to forsake their privacy for better service.

  View details for DOI 10.1016/j.copsyc.2019.08.010

  View details for PubMedID 31563799

• A Computer Adaptive Measure of Delay Discounting ASSESSMENT Mahalingam, V., Palkovics, M., Kosinski, M., Cek, I., Stillwell, D. 2018; 25 (8): 1036–55

  View details for DOI 10.1177/1073191116680448

  View details for Web of Science ID 000450364200007

• The Promotion of a Bright Future and the Prevention of a Dark Future: Time Anchored Incitements in News Articles and Facebook's Status Updates. Frontiers in psychology Garcia, D., Drejing, K., Amato, C., Kosinski, M., Sikström, S. 2018; 9: 1623

  Abstract

  Background: Research suggests that humans have the tendency to increase the valence of events when these are imagined to happen in the future, but to decrease the valence when the same events are imagined to happen in the past. This line of research, however, has mostly been conducted by asking participants to value imagined, yet probable, events. Our aim was to re-examine this time-valence asymmetry using real-life data: a Reuter's news and a Facebook status updates corpus. Method: We organized the Reuter news (120,000,000 words) and the Facebook status updates data (41,056,346 words) into contexts grouped in chronological order (i.e., past, present, and future) using verbs and years as time markers. These contexts were used to estimate the valence of each article and status update, respectively, in relation to the time markers using natural language processing tools (i.e., the Latent Semantic Analysis algorithm). Results: Our results using verbs, in both text corpus, showed that valence for the future was significantly higher compared to the past (future > past). Similarly, in the Reuter year condition, valence increased approximately linear from 1994 to 1999 for texts written 1996-1997. In the Facebook year condition, the valence of the future was also significantly higher than past valence. Conclusion: Generally, the analyses of the Reuters data indicated that the past is devaluated relative to both the present and the future, while the analyses of the Facebook data indicated that both the past and the present are devaluated against the future. On this basis, we suggest that people strive to communicate the promotion of a bright future and the prevention of a dark future, which in turn leads to a temporal-valence asymmetrical phenomenon (valence = past < present < future). " I have a dream that one day this nation will rise up and live out the true meaning of its creed: "We hold these truths to be self-evident, that all men are created equal."I have a dream that one day on the red hills of Georgia, the sons of former slaves and the sons of former slave owners will be able to sit down together at the table of brotherhood.I have a dream that one day even the state of Mississippi, a state sweltering with the heat of injustice, sweltering with the heat of oppression, will be transformed into an oasis of freedom and justice.I have a dream that my four little children will one day live in a nation where they will not be judged by the color of their skin but by the content of their character.I have a dream today!"Martin Luther King, Jr., 28th of August 1963, at the Lincoln Memorial, Washington, DC, United States.

  View details for DOI 10.3389/fpsyg.2018.01623

  View details for PubMedID 30271358

  View details for PubMedCentralID PMC6146082

• In Your Eyes Only? Discrepancies and Agreement Between Self- and Other-Reports of Personality From Age 14 to 29 JOURNAL OF PERSONALITY AND SOCIAL PSYCHOLOGY Rohrer, J. M., Egloff, B., Kosinski, M., Stillwell, D., Schmukle, S. C. 2018; 115 (2): 304–20

  Abstract

  Do others perceive the personality changes that take place between the ages of 14 and 29 in a similar fashion as the aging person him- or herself? This cross-sectional study analyzed age trajectories in self- versus other-reported Big Five personality traits and in self-other agreement in a sample of more than 10,000 individuals from the myPersonality Project. Results for self-reported personality showed maturation effects (increases in extraversion, conscientiousness, openness to experience, and emotional stability), and this pattern was generally also reflected in other-reports, albeit with discrepancies regarding timing and magnitude. Age differences found for extraversion were similar between the self- and other-reports, but the increase found in self-reported conscientiousness was delayed in other-reports, and the curvilinear increase found in self-reported openness was slightly steeper in other-reports. Only emotional stability showed a distinct mismatch with an increase in self-reports, but no significant age effect in other-reports. Both the self- and other-reports of agreeableness showed no significant age trends. The trait correlations between the self- and other-reports increased with age for emotional stability, openness, agreeableness, and conscientiousness; by contrast, agreement regarding extraversion remained stable. The profile correlations confirmed increases in self-other agreement with age. We suggest that these gains in agreement are a further manifestation of maturation. Taken together, our analyses generally show commonalities but also some divergences in age-associated mean level changes between self- and other-reports of the Big Five, as well as an age trend toward increasing self-other agreement. (PsycINFO Database Record

  View details for PubMedID 28206791

• Musical Preferences Predict Personality: Evidence From Active Listening and Facebook Likes PSYCHOLOGICAL SCIENCE Nave, G., Minxha, J., Greenberg, D. M., Kosinski, M., Stillwell, D., Rentfrow, J. 2018; 29 (7): 1145–58

  Abstract

  Research over the past decade has shown that various personality traits are communicated through musical preferences. One limitation of that research is external validity, as most studies have assessed individual differences in musical preferences using self-reports of music-genre preferences. Are personality traits communicated through behavioral manifestations of musical preferences? We addressed this question in two large-scale online studies with demographically diverse populations. Study 1 ( N = 22,252) shows that reactions to unfamiliar musical excerpts predicted individual differences in personality-most notably, openness and extraversion-above and beyond demographic characteristics. Moreover, these personality traits were differentially associated with particular music-preference dimensions. The results from Study 2 ( N = 21,929) replicated and extended these findings by showing that an active measure of naturally occurring behavior, Facebook Likes for musical artists, also predicted individual differences in personality. In general, our findings establish the robustness and external validity of the links between musical preferences and personality.

  View details for PubMedID 29587129

• One Size Fits All: Context Collapse, Self-Presentation Strategies and Language Styles on Facebook JOURNAL OF COMPUTER-MEDIATED COMMUNICATION Gil-Lopez, T., Shen, C., Benefield, G. A., Palomares, N. A., Kosinski, M., Stillwell, D. 2018; 23 (3): 127–45

  View details for DOI 10.1093/jcmc/zmy006

  View details for Web of Science ID 000434876800001

• The Language of Religious Affiliation: Social, Emotional, and Cognitive Differences SOCIAL PSYCHOLOGICAL AND PERSONALITY SCIENCE Yaden, D. B., Eichstaedt, J. C., Kern, M. L., Smith, L. K., Buffone, A., Stillwell, D. J., Kosinski, M., Ungar, L. H., Seligman, M. P., Schwartz, H. 2018; 9 (4): 444–52

  View details for DOI 10.1177/1948550617711228

  View details for Web of Science ID 000439615800008

• Editorial overview: Big data in the behavioral sciences (vol 18, pg 1, 2017) CURRENT OPINION IN BEHAVIORAL SCIENCES Kosinski, M., Behrend, T. 2018; 19: 124–26

  View details for Web of Science ID 000428954900023

• Usage patterns and social circles on Facebook among elderly people with diverse personality traits EDUCATIONAL GERONTOLOGY Mo, F., Zhou, J., Kosinski, M., Stillwell, D. 2018; 44 (4): 265–75

  View details for DOI 10.1080/03601277.2018.1459088

  View details for Web of Science ID 000432154700007

• Latent human traits in the language of social media: An open-vocabulary approach. PloS one Kulkarni, V., Kern, M. L., Stillwell, D., Kosinski, M., Matz, S., Ungar, L., Skiena, S., Schwartz, H. A. 2018; 13 (11): e0201703

  Abstract

  Over the past century, personality theory and research has successfully identified core sets of characteristics that consistently describe and explain fundamental differences in the way people think, feel and behave. Such characteristics were derived through theory, dictionary analyses, and survey research using explicit self-reports. The availability of social media data spanning millions of users now makes it possible to automatically derive characteristics from behavioral data-language use-at large scale. Taking advantage of linguistic information available through Facebook, we study the process of inferring a new set of potential human traits based on unprompted language use. We subject these new traits to a comprehensive set of evaluations and compare them with a popular five factor model of personality. We find that our language-based trait construct is often more generalizable in that it often predicts non-questionnaire-based outcomes better than questionnaire-based traits (e.g. entities someone likes, income and intelligence quotient), while the factors remain nearly as stable as traditional factors. Our approach suggests a value in new constructs of personality derived from everyday human language use.

  View details for PubMedID 30485276

• Building a profile of subjective well-being for social media users PLOS ONE Chen, L., Gong, T., Kosinski, M., Stillwell, D., Davidson, R. L. 2017; 12 (11): e0187278

  Abstract

  Subjective well-being includes 'affect' and 'satisfaction with life' (SWL). This study proposes a unified approach to construct a profile of subjective well-being based on social media language in Facebook status updates. We apply sentiment analysis to generate users' affect scores, and train a random forest model to predict SWL using affect scores and other language features of the status updates. Results show that: the computer-selected features resemble the key predictors of SWL as identified in early studies; the machine-predicted SWL is moderately correlated with the self-reported SWL (r = 0.36, p < 0.01), indicating that language-based assessment can constitute valid SWL measures; the machine-assessed affect scores resemble those reported in a previous experimental study; and the machine-predicted subjective well-being profile can also reflect other psychological traits like depression (r = 0.24, p < 0.01). This study provides important insights for psychological prediction using multiple, machine-assessed components and longitudinal or dense psychological assessment using social media language.

  View details for PubMedID 29135991

• Frankly, We Do Give a Damn: The Relationship Between Profanity and Honesty. Social psychological and personality science Feldman, G., Lian, H., Kosinski, M., Stillwell, D. 2017; 8 (7): 816-826

  Abstract

  There are two conflicting perspectives regarding the relationship between profanity and dishonesty. These two forms of norm-violating behavior share common causes and are often considered to be positively related. On the other hand, however, profanity is often used to express one's genuine feelings and could therefore be negatively related to dishonesty. In three studies, we explored the relationship between profanity and honesty. We examined profanity and honesty first with profanity behavior and lying on a scale in the lab (Study 1; N = 276), then with a linguistic analysis of real-life social interactions on Facebook (Study 2; N = 73,789), and finally with profanity and integrity indexes for the aggregate level of U.S. states (Study 3; N = 50 states). We found a consistent positive relationship between profanity and honesty; profanity was associated with less lying and deception at the individual level and with higher integrity at the society level.

  View details for DOI 10.1177/1948550616681055

  View details for PubMedID 29187959

  View details for PubMedCentralID PMC5686790

• Living in the Past, Present, and Future: Measuring Temporal Orientation With Language JOURNAL OF PERSONALITY Park, G., Schwartz, H. A., Sap, M., Kern, M. L., Weingarten, E., Eichstaedt, J. C., Berger, J., Stillwell, D. J., Kosinski, M., Ungar, L. H., Seligman, M. E. 2017; 85 (2): 270-280

  Abstract

  Temporal orientation refers to individual differences in the relative emphasis one places on the past, present, or future, and it is related to academic, financial, and health outcomes. We propose and evaluate a method for automatically measuring temporal orientation through language expressed on social media. Judges rated the temporal orientation of 4,302 social media messages. We trained a classifier based on these ratings, which could accurately predict the temporal orientation of new messages in a separate validation set (accuracy/mean sensitivity = .72; mean specificity = .77). We used the classifier to automatically classify 1.3 million messages written by 5,372 participants (50% female; ages 13-48). Finally, we tested whether individual differences in past, present, and future orientation differentially related to gender, age, Big Five personality, satisfaction with life, and depressive symptoms. Temporal orientations exhibit several expected correlations with age, gender, and Big Five personality. More future-oriented people were older, more likely to be female, more conscientious, less impulsive, less depressed, and more satisfied with life; present orientation showed the opposite pattern. Language-based assessments can complement and extend existing measures of temporal orientation, providing an alternative approach and additional insights into language and personality relationships.

  View details for DOI 10.1111/jopy.12239

  View details for Web of Science ID 000397890200012

• A Computer Adaptive Measure of Delay Discounting. Assessment Mahalingam, V., Palkovics, M., Kosinski, M., Cek, I., Stillwell, D. 2016

  Abstract

  Delay discounting has been linked to important behavioral, health, and social outcomes, including academic achievement, social functioning and substance use, but thoroughly measuring delay discounting is tedious and time consuming. We develop and consistently validate an efficient and psychometrically sound computer adaptive measure of discounting. First, we develop a binary search-type algorithm to measure discounting using a large international data set of 4,190 participants. Using six independent samples (N = 1,550), we then present evidence of concurrent validity with two standard measures of discounting and a measure of discounting real rewards, convergent validity with addictive behavior, impulsivity, personality, survival probability; and divergent validity with time perspective, life satisfaction, age and gender. The new measure is considerably shorter than standard questionnaires, includes a range of time delays, can be applied to multiple reward magnitudes, shows excellent concurrent, convergent, divergent, and discriminant validity-by showing more sensitivity to effects of smoking behavior on discounting.

  View details for PubMedID 27886981

• A decade into Facebook: where is psychiatry in the digital age? The lancet. Psychiatry Inkster, B., Stillwell, D., Kosinski, M., Jones, P. 2016; 3 (11): 1087-1090

  View details for DOI 10.1016/S2215-0366(16)30041-4

  View details for PubMedID 27794373

• The Song Is You: Preferences for Musical Attribute Dimensions Reflect Personality SOCIAL PSYCHOLOGICAL AND PERSONALITY SCIENCE Greenberg, D. M., Kosinski, M., Stillwell, D. J., Monteiro, B. L., Levitin, D. J., Rentfrow, P. J. 2016; 7 (6): 597-605

  View details for DOI 10.1177/1948550616641473

  View details for Web of Science ID 000381035700012

• Self-Monitoring and the Metatraits JOURNAL OF PERSONALITY Wilmot, M. P., DeYoung, C. G., Stillwell, D., Kosinski, M. 2016; 84 (3): 335-347

  Abstract

  Prior attempts at locating self-monitoring within general taxonomies of personality traits have largely proved unsuccessful. However, past research has typically neglected (a) the bidimensionality of the Self-Monitoring Scale and (b) the hierarchical nature of personality. The objective of this study was to test hypotheses that the two self-monitoring factors are located at the level of the metatraits. Using data from two large multi-informant samples, one community (Sample 1: N = 552, Mage  = 51.26, 61% female; NPeers  = 1,551, Mage  = 48.61, 37% female) and one online (Sample 2: N = 3,726, Mage  = 24.89, 59% female; NPeers  = 17,868, Mage  = 26.23, 64% female), confirmatory factor analysis was used to test the hypotheses. Results confirmed hypotheses that acquisitive self-monitoring would have a strong positive relation to metatrait Plasticity, whereas protective self-monitoring would have a moderate negative relation to metatrait Stability. In both samples, constraining the correlation between acquisitive self-monitoring and Plasticity to unity did not alter model fit indices, indicating that the two putatively distinct constructs are identical. Findings have wide-ranging implications, including integration of the construct of self-monitoring into the mainstream of personality research, as the latter moves toward the development of broad explanatory theories.

  View details for DOI 10.1111/jopy.12162

  View details for Web of Science ID 000375937400006

  View details for PubMedID 25565551

• Computational personality recognition in social media USER MODELING AND USER-ADAPTED INTERACTION Farnadi, G., Sitaraman, G., Sushmita, S., Celli, F., Kosinski, M., Stillwell, D., Davalos, S., Moens, M., De Cock, M. 2016; 26 (2-3): 109-142

  View details for DOI 10.1007/s11257-016-9171-0

  View details for Web of Science ID 000376432700002

• Characterizing a psychiatric symptom dimension related to deficits in goal-directed control. eLife Gillan, C. M., Kosinski, M., Whelan, R., Phelps, E. A., Daw, N. D. 2016; 5

  Abstract

  Prominent theories suggest that compulsive behaviors, characteristic of obsessive-compulsive disorder and addiction, are driven by shared deficits in goal-directed control, which confers vulnerability for developing rigid habits. However, recent studies have shown that deficient goal-directed control accompanies several disorders, including those without an obvious compulsive element. Reasoning that this lack of clinical specificity might reflect broader issues with psychiatric diagnostic categories, we investigated whether a dimensional approach would better delineate the clinical manifestations of goal-directed deficits. Using large-scale online assessment of psychiatric symptoms and neurocognitive performance in two independent general-population samples, we found that deficits in goal-directed control were most strongly associated with a symptom dimension comprising compulsive behavior and intrusive thought. This association was highly specific when compared to other non-compulsive aspects of psychopathology. These data showcase a powerful new methodology and highlight the potential of a dimensional, biologically-grounded approach to psychiatry research.

  View details for DOI 10.7554/eLife.11305

  View details for PubMedID 26928075

  View details for PubMedCentralID PMC4786435

• Living in the Past, Present, and Future: Measuring Temporal Orientation With Language. Journal of personality Park, G., Schwartz, H. A., Sap, M., Kern, M. L., Weingarten, E., Eichstaedt, J. C., Berger, J., Stillwell, D. J., Kosinski, M., Ungar, L. H., Seligman, M. E. 2015

  Abstract

  Temporal orientation refers to individual differences in the relative emphasis one places on the past, present, or future, and it is related to academic, financial, and health outcomes. We propose and evaluate a method for automatically measuring temporal orientation through language expressed on social media. Judges rated the temporal orientation of 4,302 social media messages. We trained a classifier based on these ratings, which could accurately predict the temporal orientation of new messages in a separate validation set (accuracy/mean sensitivity = .72; mean specificity = .77). We used the classifier to automatically classify 1.3 million messages written by 5,372 participants (50% female; ages 13-48). Finally, we tested whether individual differences in past, present, and future orientation differentially related to gender, age, Big Five personality, satisfaction with life, and depressive symptoms. Temporal orientations exhibit several expected correlations with age, gender, and Big Five personality. More future-oriented people were older, more likely to be female, more conscientious, less impulsive, less depressed, and more satisfied with life; present orientation showed the opposite pattern. Language-based assessments can complement and extend existing measures of temporal orientation, providing an alternative approach and additional insights into language and personality relationships.

  View details for DOI 10.1111/jopy.12239

  View details for PubMedID 26710321

• Using Item Response Theory to Develop Measures of Acquisitive and Protective Self-Monitoring From the Original Self-Monitoring Scale. Assessment Wilmot, M. P., Kostal, J. W., Stillwell, D., Kosinski, M. 2015

  Abstract

  For the past 40 years, the conventional univariate model of self-monitoring has reigned as the dominant interpretative paradigm in the literature. However, recent findings associated with an alternative bivariate model challenge the conventional paradigm. In this study, item response theory is used to develop measures of the bivariate model of acquisitive and protective self-monitoring using original Self-Monitoring Scale (SMS) items, and data from two large, nonstudent samples (Ns = 13,563 and 709). Results indicate that the new acquisitive (six-item) and protective (seven-item) self-monitoring scales are reliable, unbiased in terms of gender and age, and demonstrate theoretically consistent relations to measures of personality traits and cognitive ability. Additionally, by virtue of using original SMS items, previously collected responses can be reanalyzed in accordance with the alternative bivariate model. Recommendations for the reanalysis of archival SMS data, as well as directions for future research, are provided.

  View details for PubMedID 26603117

• Musical Preferences are Linked to Cognitive Styles PLOS ONE Greenberg, D. M., Baron-Cohen, S., Stillwell, D. J., Kosinski, M., Rentfrow, P. J. 2015; 10 (7)

  Abstract

  Why do we like the music we do? Research has shown that musical preferences and personality are linked, yet little is known about other influences on preferences such as cognitive styles. To address this gap, we investigated how individual differences in musical preferences are explained by the empathizing-systemizing (E-S) theory. Study 1 examined the links between empathy and musical preferences across four samples. By reporting their preferential reactions to musical stimuli, samples 1 and 2 (Ns = 2,178 and 891) indicated their preferences for music from 26 different genres, and samples 3 and 4 (Ns = 747 and 320) indicated their preferences for music from only a single genre (rock or jazz). Results across samples showed that empathy levels are linked to preferences even within genres and account for significant proportions of variance in preferences over and above personality traits for various music-preference dimensions. Study 2 (N = 353) replicated and extended these findings by investigating how musical preferences are differentiated by E-S cognitive styles (i.e., 'brain types'). Those who are type E (bias towards empathizing) preferred music on the Mellow dimension (R&B/soul, adult contemporary, soft rock genres) compared to type S (bias towards systemizing) who preferred music on the Intense dimension (punk, heavy metal, and hard rock). Analyses of fine-grained psychological and sonic attributes in the music revealed that type E individuals preferred music that featured low arousal (gentle, warm, and sensual attributes), negative valence (depressing and sad), and emotional depth (poetic, relaxing, and thoughtful), while type S preferred music that featured high arousal (strong, tense, and thrilling), and aspects of positive valence (animated) and cerebral depth (complexity). The application of these findings for clinicians, interventions, and those on the autism spectrum (largely type S or extreme type S) are discussed.

  View details for DOI 10.1371/journal.pone.0131151

  View details for Web of Science ID 000358597100012

  View details for PubMedID 26200656

  View details for PubMedCentralID PMC4511638

• Do Facebook Status Updates Reflect Subjective Well-Being? CYBERPSYCHOLOGY BEHAVIOR AND SOCIAL NETWORKING Liu, P., Tov, W., Kosinski, M., Stillwell, D. J., Qiu, L. 2015; 18 (7): 373-379

  Abstract

  Nowadays, millions of people around the world use social networking sites to express everyday thoughts and feelings. Many researchers have tried to make use of social media to study users' online behaviors and psychological states. However, previous studies show mixed results about whether self-generated contents on Facebook reflect users' subjective well-being (SWB). This study analyzed Facebook status updates to determine the extent to which users' emotional expression predicted their SWB-specifically their self-reported satisfaction with life. It was found that positive emotional expressions on Facebook did not correlate with life satisfaction, whereas negative emotional expressions within the past 9-10 months (but not beyond) were significantly related to life satisfaction. These findings suggest that both the type of emotional expressions and the time frame of status updates determine whether emotional expressions in Facebook status updates can effectively reflect users' SWB. The findings shed light on the characteristics of online social media and improve the understanding of how user-generated contents reflect users' psychological states.

  View details for DOI 10.1089/cyber.2015.0022

  View details for Web of Science ID 000363896300003

  View details for PubMedID 26167835

• Tracking the Digital Footprints of Personality PROCEEDINGS OF THE IEEE Lambiotte, R., Kosinski, M. 2014; 102 (12): 1934-1939

  View details for DOI 10.1109/JPROC.2014.2359054

  View details for Web of Science ID 000345524100008