Gabriella Harari is an Assistant Professor in the Department of Communication at Stanford University, where she directs the Media and Personality Lab.

She studies how personality is expressed in the physical and digital contexts of everyday life. Much of her research is focused on understanding what digital technologies reveal about who we are, and how use of digital technologies shapes who we are. Her current projects analyze people’s everyday behavioral patterns (e.g., social interactions, mobility) and environmental contexts (e.g., places visited, social media platforms) to show how they are associated with individual differences in personality and well-being.

Harari takes an ecological approach to conducting her research, emphasizing the importance of studying people and their behavior in natural contexts. To that end, she conducts intensive longitudinal field studies and is interested in mobile sensing methods and analytic techniques that combine approaches from the social and computer sciences. For example, methodologies she uses in her work in include surveys, experience sampling, longitudinal modeling, mobile sensing, data mining, and machine learning.

Harari completed a Postdoctoral Fellowship and earned her PhD at the Department of Psychology at The University of Texas at Austin. She completed her BA in Psychology & Humanities from Florida International University, where she was also a Ronald E. McNair Scholar. Her work has been published in academic outlets such as Perspectives in Psychological Science, Journal of Personality and Social Psychology, and the Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT). Her work has also been supported by the National Science Foundation and Stanford HAI Seed Grant Awards.

Academic Appointments

Professional Education

  • BA, Florida International University, Psychology & Humanities (2011)
  • PhD, The University of Texas at Austin, Psychology (2016)

Stanford Advisees

All Publications

  • Identity development in the digital context SOCIAL AND PERSONALITY PSYCHOLOGY COMPASS Soh, S., Talaifar, S., Harari, G. M. 2024; 18 (2)

    View details for DOI 10.1111/spc3.12940

    View details for Web of Science ID 001162650900001

  • Understanding behaviours in context using mobile sensing NATURE REVIEWS PSYCHOLOGY Harari, G. M., Gosling, S. D. 2023; 2 (12): 767-779
  • Situating smartphones in daily life: Big Five traits and contexts associated with young adults' smartphone use. Journal of personality and social psychology Roehrick, K. C., Vaid, S. S., Harari, G. M. 2023; 125 (5): 1096-1118


    We examine individual differences in smartphone behavior to understand the independent effects of Big Five traits and four different contextual factors (places, people, co-occurring activities, and psychological situations) on the frequency and duration of smartphone use in daily life. Using survey, experience sampling, and mobile sensing data collected over the span of 2 weeks from two samples of college students (Sample 1, N = 634; Sample 2, N = 211), we conducted a series of multilevel Bayesian gamma hurdle and negative binomial hurdle models to explain smartphone use (vs. nonuse) and the degree of use. Our pooled findings suggest that extraversion was associated with more frequent use, while conscientiousness was associated with smartphone nonuse and shorter durations of use. In terms of context, our findings show that smartphones were used more frequently when people were out and about in public places (e.g., cafes, stores) and less frequently in particularly social places (e.g., bars, friends' houses). Smartphones were also used more frequently with weak ties (e.g., classmates, coworkers) and less frequently with close ties (e.g., roommates, family, significant others). Smartphones were also used less and for shorter durations when people were engaged in certain activities (e.g., studying, commuting, chores, exercising), and when in situations perceived to be romantic or involving work. We discuss the findings with regard to past work on smartphone use and describe the next steps for research on smartphone behavior. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

    View details for DOI 10.1037/pspp0000478

    View details for PubMedID 37956069

  • Well-Being in Social Interactions: Examining Personality-Situation Dynamics in Face-to-Face and Computer-Mediated Communication JOURNAL OF PERSONALITY AND SOCIAL PSYCHOLOGY Kroencke, L., Harari, G. M., Back, M. D., Wagner, J. 2023; 124 (2): 437-460


    Decades of research show that people's social lives are linked to their well-being. Yet, research on the relationship between social interactions and well-being has been largely inconclusive with regard to the effects of person-situation interactions, such as the interplay between contextual factors (e.g., interactions occurring in physical vs. digital contexts, different interaction partners) and dispositional tendencies (e.g., Big Five personality traits). Here, we report on exploratory and confirmatory findings from three large studies of college students (Study 1: N = 1,360; Study 2: N = 851; Study 3: N = 864) who completed a total of 139,363 experience sampling surveys (reporting on 87,976 social interactions). We focus on the effects of different modes of communication (face-to-face [FtF] interactions, computer-mediated communication [CMC], and mixed episodes [FtF + CMC]), and types of interaction partners (close peers, family members, and weak ties). Using multilevel structural equation modeling, we found that FtF interactions and mixed episodes were associated with highest well-being on the within-person level, and that these effects were particularly pronounced for individuals with high levels of neuroticism. CMC was related to lower well-being than FtF interactions, but higher well-being than not socializing at all. Regarding the type of interaction partner, individuals reported higher well-being after interactions with close peers than after interactions with family members and weak ties, and the difference between close peers and weak ties was larger for FtF interactions than for CMC. We discuss these findings with regard to theories of person-situation interactions and research on well-being and social interactions. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

    View details for DOI 10.1037/pspp0000422

    View details for Web of Science ID 000917161900010

    View details for PubMedID 35834202

  • Investigating the Within-Person Structure and Correlates of Emotional Experiences in Everyday Life Using an Emotion Family Approach JOURNAL OF PERSONALITY AND SOCIAL PSYCHOLOGY Chung, J. M., Harari, G. M., Denissen, J. A. 2022; 122 (6): 1146-1189
  • Personality-Place Transactions: Mapping the Relationships Between Big Five Personality Traits, States, and Daily Places JOURNAL OF PERSONALITY AND SOCIAL PSYCHOLOGY Matz, S. C., Harari, G. M. 2021; 120 (5): 1367-1385


    People actively select their environments, and the environments they select can alter their psychological characteristics in the moment and over time. Such dynamic person-environment transactions are likely to play out in the context of daily life via the places people spend time in (e.g., home, work, or public places like cafes and restaurants). This article investigates personality-place transactions at 3 conceptual levels: stable personality traits, momentary personality states, and short-term personality trait expressions. Three 2-week experience sampling studies (2 exploratory and 1 confirmatory with a total N = 2,350 and more than 63,000 momentary assessments) were used to provide the first large-scale evidence showing that people's stable Big Five traits are associated with the frequency with which they visit different places on a daily basis. For example, extraverted people reported spending less time at home and more time at cafés, bars, and friends' houses. The findings also show that spending time in a particular place predicts people's momentary personality states and their short-term trait expression over time. For example, people reported feeling more extraverted in the moment when spending time at bars/parties, cafés/restaurants, or friends' houses, compared with when at home. People who showed preferences for spending more time in these places also showed higher levels of short-term trait extraversion over the course of 2 weeks. The findings make theoretical contributions to environmental psychology, personality dynamics, as well as the person-environment transactions literature, and highlight practical implications for a world in which the places people visit can be easily captured via GPS sensors. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

    View details for DOI 10.1037/pspp0000297

    View details for Web of Science ID 000668228800010

    View details for PubMedID 32496085

  • Who uses what and how often?: Personality predictors of multiplatform social media use among young adults JOURNAL OF RESEARCH IN PERSONALITY Vaid, S. S., Harari, G. M. 2021; 91
  • Personality Sensing for Theory Development and Assessment in the Digital Age EUROPEAN JOURNAL OF PERSONALITY Harari, G. M., Vaid, S. S., Mueller, S. R., Stachl, C., Marrero, Z., Schoedel, R., Buehner, M., Gosling, S. D. 2020

    View details for DOI 10.1002/per.2273

    View details for Web of Science ID 000571158800001

  • Investigating the Relationships Between Mobility Behaviours and Indicators of Subjective Well-Being Using Smartphone-Based Experience Sampling and GPS Tracking EUROPEAN JOURNAL OF PERSONALITY Mueller, S. R., Peters, H., Matz, S. C., Wang, W., Harari, G. M. 2020; 34 (5): 714–32

    View details for DOI 10.1002/per.2262

    View details for Web of Science ID 000585339000008

  • Predicting personality from patterns of behavior collected with smartphones. Proceedings of the National Academy of Sciences of the United States of America Stachl, C., Au, Q., Schoedel, R., Gosling, S. D., Harari, G. M., Buschek, D., Volkel, S. T., Schuwerk, T., Oldemeier, M., Ullmann, T., Hussmann, H., Bischl, B., Buhner, M. 2020


    Smartphones enjoy high adoption rates around the globe. Rarely more than an arm's length away, these sensor-rich devices can easily be repurposed to collect rich and extensive records of their users' behaviors (e.g., location, communication, media consumption), posing serious threats to individual privacy. Here we examine the extent to which individuals' Big Five personality dimensions can be predicted on the basis of six different classes of behavioral information collected via sensor and log data harvested from smartphones. Taking a machine-learning approach, we predict personality at broad domain ([Formula: see text] = 0.37) and narrow facet levels ([Formula: see text] = 0.40) based on behavioral data collected from 624 volunteers over 30 consecutive days (25,347,089 logging events). Our cross-validated results reveal that specific patterns in behaviors in the domains of 1) communication and social behavior, 2) music consumption, 3) app usage, 4) mobility, 5) overall phone activity, and 6) day- and night-time activity are distinctively predictive of the Big Five personality traits. The accuracy of these predictions is similar to that found for predictions based on digital footprints from social media platforms and demonstrates the possibility of obtaining information about individuals' private traits from behavioral patterns passively collected from their smartphones. Overall, our results point to both the benefits (e.g., in research settings) and dangers (e.g., privacy implications, psychological targeting) presented by the widespread collection and modeling of behavioral data obtained from smartphones.

    View details for DOI 10.1073/pnas.1920484117

    View details for PubMedID 32665436

  • Sensing Sociability: Individual Differences in Young Adults' Conversation, Calling, Texting, and App Use Behaviors in Daily Life JOURNAL OF PERSONALITY AND SOCIAL PSYCHOLOGY Harari, G. M., Mueller, S. R., Stachl, C., Wang, R., Wang, W., Buehner, M., Rentfrow, P. J., Campbell, A. T., Gosling, S. D. 2020; 119 (1): 204–28


    Sociability as a disposition describes a tendency to affiliate with others (vs. be alone). Yet, we know relatively little about how much social behavior people engage in during a typical day. One challenge to documenting social behavior tendencies is the broad number of channels over which socializing can occur, both in-person and through digital media. To examine individual differences in everyday social behavior patterns, here we used smartphone-based mobile sensing methods (MSMs) in four studies (total N = 926) to collect real-world data about young adults' social behaviors across four communication channels: conversations, phone calls, text messages, and use of messaging and social media applications. To examine individual differences, we first focused on establishing between-person variability in daily social behavior, examining stability of and relationships among daily sensed social behavior tendencies. To explore factors that may explain the observed individual differences in sensed social behavior, we then expanded our focus to include other time estimates (e.g., times of the day, days of the week) and personality traits. In doing so, we present the first large-scale descriptive portrait of behavioral sociability patterns, characterizing the degree to which young adults engaged in social behaviors and mapping these behaviors onto self-reported personality dispositions. Our discussion focuses on how the observed sociability patterns compare to previous research on young adults' social behavior. We conclude by pointing to areas for future research aimed at understanding sociability using mobile sensing and other naturalistic observation methods for the assessment of social behavior. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

    View details for DOI 10.1037/pspp0000245

    View details for Web of Science ID 000543795500010

    View details for PubMedID 31107054

  • Smartphone sensing methods for studying behavior in everyday life CURRENT OPINION IN BEHAVIORAL SCIENCES Harari, G. M., Mueller, S. R., Aung, M. H., Rentfrow, P. J. 2017; 18: 83–90
  • Psychological well-being in Europe after the outbreak of war in Ukraine. Nature communications Scharbert, J., Humberg, S., Kroencke, L., Reiter, T., Sakel, S., Ter Horst, J., Utesch, K., Gosling, S. D., Harari, G., Matz, S. C., Schoedel, R., Stachl, C., Aguilar, N. M., Amante, D., Aquino, S. D., Bastias, F., Bornamanesh, A., Bracegirdle, C., Campos, L. A., Chauvin, B., Coetzee, N., Dorfman, A., Dos Santos, M., El-Haddad, R. W., Fajkowska, M., Göncü-Köse, A., Gnisci, A., Hadjisolomou, S., Hale, W. W., Katzir, M., Khechuashvili, L., Kirchner-Häusler, A., Kotzur, P. F., Kritzler, S., Lu, J. G., Machado, G. D., Martskvishvili, K., Mottola, F., Obschonka, M., Paolini, S., Perugini, M., Rohmer, O., Saeedian, Y., Sergi, I., Shani, M., Skimina, E., Smillie, L. D., Talaifar, S., Talhelm, T., Tokat, T., Torres, A., Torres, C. V., Van Assche, J., Wei, L., Yalçın, A., van Zalk, M., Bühner, M., Back, M. D. 2024; 15 (1): 1202


    The Russian invasion of Ukraine on February 24, 2022, has had devastating effects on the Ukrainian population and the global economy, environment, and political order. However, little is known about the psychological states surrounding the outbreak of war, particularly the mental well-being of individuals outside Ukraine. Here, we present a longitudinal experience-sampling study of a convenience sample from 17 European countries (total participants = 1,341, total assessments = 44,894, countries with >100 participants = 5) that allows us to track well-being levels across countries during the weeks surrounding the outbreak of war. Our data show a significant decline in well-being on the day of the Russian invasion. Recovery over the following weeks was associated with an individual's personality but was not statistically significantly associated with their age, gender, subjective social status, and political orientation. In general, well-being was lower on days when the war was more salient on social media. Our results demonstrate the need to consider the psychological implications of the Russo-Ukrainian war next to its humanitarian, economic, and ecological consequences.

    View details for DOI 10.1038/s41467-024-44693-6

    View details for PubMedID 38378761

    View details for PubMedCentralID 8196079

  • A global experience-sampling method study of well-being during times of crisis: The CoCo project SOCIAL AND PERSONALITY PSYCHOLOGY COMPASS Scharbert, J., Reiter, T., Sakel, S., Horst, J., Geukes, K., Gosling, S. D., Harari, G., Kroencke, L., Matz, S., Schoedel, R., Shani, M., Stachl, C., Talaifar, S., Aguilar, N. A., Amante, D., Aquino, S. D., Bastias, F., Biesanz, J. C., Bornamanesh, A., Bracegirdle, C., Campos, L. M., Ceballos, M. C., Chauvin, B., Choychod, S., Coetzee, N., Costin, V., Machado, G. S., Dorfman, A., dos Santos, M., El-Haddad, R. W., Fajkowska, M., Gnisci, A., Hadjisolomou, S., Hale, W. W., Katzir, M., Khechuashvili, L., Kheirabadi, G., Kirchner-Haeusler, A., Koese, A., Kotzur, P., Kritzler, S., Lu, J. G., Martskvishvili, K., Mottola, F., Obschonka, M., Paolini, S., Perugini, M., Rohmer, O., Saeedian, Y., Sarayuthpitak, J., Sczesny, S., Sergi, I., Skimina, E., Talhelm, T., Tangdhanakanond, K., Tokat, T., Torres, A. R., Torres, C. V., Van Assche, J., Wolvaardt, G. G., Yalcin, A., Buehner, M., van Zalk, M., Back, M. D. 2023

    View details for DOI 10.1111/spc3.12813

    View details for Web of Science ID 001018262100001

  • Who Benefits From Which Activity? On the Relations Between Personality Traits, Leisure Activities, and Well-Being JOURNAL OF PERSONALITY AND SOCIAL PSYCHOLOGY Kuper, N., Kroencke, L., Harari, G. M., Denissen, J. A. 2022


    Leisure activities have been emphasized as an important predictor of well-being. However, little research has examined the effects of leisure activity enactment on well-being over time. Moreover, it is unknown which activities are most beneficial for whom. We integrate diverse theoretical accounts of person-environment relations and propose a generic Personality-Activity-Well-Being (PAW) framework, which highlights different relations between personality traits, activities, and well-being. To investigate these relations, we used 11 annual waves from the Longitudinal Internet Studies for the Social Sciences (LISS) panel (total N = 12,703 participants, N = 59,108 assessments), which included measures of the Big Five personality traits, 15 different leisure activities, and affective well-being and life satisfaction. Our preregistered multilevel models revealed three sets of findings. First, we observed on average small expected between-person associations between leisure activities and well-being (e.g., higher average levels of holidays, evening socializing, talking to close others, exercise, and cultural activities were associated with higher well-being). Annual within-person fluctuations in several leisure activities also predicted well-being in expected ways, but effect sizes were very small and varied strongly across participants. Second, personality traits were related to leisure activities in hypothesized ways, yielding on average small but also some moderate and large correlations. Third, Personality Trait × Leisure Activity interactions were only evident on the between-person level, very small in size, and in the opposite direction of our expectations. Personality traits did not moderate well-being benefits from leisure within persons. We discuss the implications of our findings and sketch an agenda for future work. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

    View details for DOI 10.1037/pspp0000438

    View details for Web of Science ID 000877780800001

    View details for PubMedID 36326676

  • Evaluating voice samples as a potential source of information about personality. Acta psychologica Marrero, Z. N., Gosling, S. D., Pennebaker, J. W., Harari, G. M. 2022; 230: 103740


    Speech is a powerful medium through which a variety of psychologically relevant phenomena are expressed. Here we take a first step in evaluating the potential of using voice samples as non-self-report measures of personality. In particular, we examine the extent to which linguistic and vocal information extracted from semi-structured vocal samples can be used to predict conventional measures of personality. We extracted 94 linguistic features (using Linquistic Inquiry Word Count, 2015) and 272 vocal features (using pyAudioAnalysis) from 614 voice samples of at least 50 words. Using a two-stage, fully automatable machine learning pipeline we evaluated the extent to which these features predicted self-report personality scales (Big Five Inventory). For comparison purposes, we also examined the predictive performance of these voice features with respect to depression, age, and gender. Results showed that voice samples accounted for 10.67% of the variance in personality traits on average and that the same samples could also predict depression, age, and gender. Moreover, the results reported here provide a conservative estimate of the degree to which features derived from voice samples could be used to predict personality traits and suggest a number of opportunities to optimize personality prediction and better understand how voice samples carry information about personality.

    View details for DOI 10.1016/j.actpsy.2022.103740

    View details for PubMedID 36126377

  • Analyzing GPS Data for Psychological Research: A Tutorial ADVANCES IN METHODS AND PRACTICES IN PSYCHOLOGICAL SCIENCE Muller, S. R., Bayer, J. B., Ross, M., Mount, J., Stachl, C., Harari, G. M., Chang, Y., Le, H. K. 2022; 5 (2)
  • Multi-modal data collection for measuring health, behavior, and living environment of large-scale participant cohorts. GigaScience Wu, C., Fritz, H., Bastami, S., Maestre, J. P., Thomaz, E., Julien, C., Castelli, D. M., de Barbaro, K., Bearman, S. K., Harari, G. M., Cameron Craddock, R., Kinney, K. A., Gosling, S. D., Schnyer, D. M., Nagy, Z. 2021; 10 (6)


    BACKGROUND: As mobile technologies become ever more sensor-rich, portable, and ubiquitous, data captured by smart devices are lending rich insights into users' daily lives with unprecedented comprehensiveness and ecological validity. A number of human-subject studies have been conducted to examine the use of mobile sensing to uncover individual behavioral patterns and health outcomes, yet minimal attention has been placed on measuring living environments together with other human-centered sensing data. Moreover, the participant sample size in most existing studies falls well below a few hundred, leaving questions open about the reliability of findings on the relations between mobile sensing signals and human outcomes.RESULTS: To address these limitations, we developed a home environment sensor kit for continuous indoor air quality tracking and deployed it in conjunction with smartphones, Fitbits, and ecological momentary assessments in a cohort study of up to 1,584 college student participants per data type for 3 weeks. We propose a conceptual framework that systematically organizes human-centric data modalities by their temporal coverage and spatial freedom. Then we report our study procedure, technologies and methods deployed, and descriptive statistics of the collected data that reflect the participants' mood, sleep, behavior, and living environment.CONCLUSIONS: We were able to collect from a large participant cohort satisfactorily complete multi-modal sensing and survey data in terms of both data continuity and participant adherence. Our novel data and conceptual development provide important guidance for data collection and hypothesis generation in future human-centered sensing studies.

    View details for DOI 10.1093/gigascience/giab044

    View details for PubMedID 34155505

  • Personality Research and Assessment in the Era of Machine Learning EUROPEAN JOURNAL OF PERSONALITY Stachl, C., Pargent, F., Hilbert, S., Harari, G. M., Schoedel, R., Vaid, S., Gosling, S. D., Buehner, M. 2020

    View details for DOI 10.1002/per.2257

    View details for Web of Science ID 000535945200001

  • Social Sensing: Assessing Social Functioning of Patients Living with Schizophrenia using Mobile Phone Sensing Wang, W., Mirjafari, S., Harari, G., Ben-Zeev, D., Brian, R., Choudhury, T., Hauser, M., Kane, J., Masaba, K., Nepal, S., Sano, A., Scherer, E., Tseng, V., Wang, R., Wen, H., Wu, J., Campbell, A., ACM ASSOC COMPUTING MACHINERY. 2020
  • A process-oriented approach to respecting privacy in the context of mobile phone tracking. Current opinion in psychology Harari, G. M. 2019; 31: 141–47


    Mobile phone tracking poses challenges to individual privacy because a phone's sensor data and metadata logs can reveal behavioral, contextual, and psychological information about the individual who uses the phone. Here, I argue for a process-oriented approach to respecting individual privacy in the context of mobile phone tracking by treating informed consent as a process, not a mouse click. This process-oriented approach allows individuals to exercise their privacy preferences and requires the design of self-tracking systems that facilitate transparency, opt-in default settings, and individual control over personal data, especially with regard to: (1) what kinds of personal data are being collected and (2) how the data are being used and shared. In sum, I argue for the development of self-tracking systems that put individual user privacy and control at their core, while enabling people to harness their personal data for self-insight and behavior change. This approach to mobile phone privacy is a radical departure from current standard data practices and has implications for a wide range of stakeholders, including individual users, researchers, and corporations.

    View details for DOI 10.1016/j.copsyc.2019.09.007

    View details for PubMedID 31693976

  • Personality trait predictors and mental well-being correlates of exercise frequency across the academic semester. Social science & medicine (1982) Kroencke, L. n., Harari, G. M., Katana, M. n., Gosling, S. D. 2019; 236: 112400


    Regular exercise is frequently recommended as a means of combating the negative effects of stress on mental health. But, among college students, exercise frequency remains below recommended levels.To better understand exercising behaviors in college students, we examined how exercise patterns change across an academic semester and how these changes relate to personality traits and mental well-being.We conducted two longitudinal experience sampling studies, using data from four cohorts of students, spanning four semesters (Fall 2015 - Spring 2017). In Study 1, a large sample of United States college students (cohort 1; N = 1126) reported the number of days they exercised and their levels of happiness, stress, sadness, and anxiety each week over the course of one academic semester (13 weeks). Study 2 (cohorts 2-4; N = 1973) was conducted to replicate our exploratory results from Study 1.Using latent growth curve modeling, we observed the same normative pattern of change across both studies: The average student exercised twice during the first week of the semester and showed consistent decreases in exercise frequency in following weeks. Across both studies, higher initial levels of exercise frequency at the start of the semester were consistently related to higher extraversion, higher conscientiousness, and lower neuroticism. Furthermore, exercise frequency and mental well-being fluctuated together after controlling for time trends in the data: In weeks during which students exercised more than predicted, they also reported being happier and less anxious.We contextualize the findings with regard to past research and discuss how they can be applied in behavior change interventions to promote students' well-being.

    View details for DOI 10.1016/j.socscimed.2019.112400

    View details for PubMedID 31336217

  • Smartphones in Personal Informatics: A Framework for Self-Tracking Research with Mobile Sensing DIGITAL PHENOTYPING AND MOBILE SENSING: NEW DEVELOPMENTS IN PSYCHOINFORMATICS Vaid, S. S., Harari, G. M., Baumeister, H., Montag, C. 2019: 65–92
  • Inference of Big-Five Personality Using Large-scale Networked Mobile and Appliance Data Tong, C., Harari, G. M., Chieh, A., Bellahsen, O., Vegreville, M., Roitmann, E., Lane, N. D., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2018: 530
  • An Evaluation of Students' Interest in and Compliance With Self-Tracking Methods: Recommendations for Incentives Based on Three Smartphone Sensing Studies SOCIAL PSYCHOLOGICAL AND PERSONALITY SCIENCE Harari, G. M., Mueller, S. R., Mishra, V., Wang, R., Campbell, A. T., Rentfrow, P. J., Gosling, S. D. 2017; 8 (5): 479–92
  • Using Human Raters to Characterize the Psychological Characteristics of GPS-based Places Muller, S. R., Matz, S., Mascolo, C., Harari, G. M., Khambatta, P., Gosling, S. D., Mehrotra, A., Musolesi, M., Rentfrow, P. J., ACM ASSOC COMPUTING MACHINERY. 2017: 157–60
  • Participants' Compliance and Experiences with Self-Tracking Using a Smartphone Sensing App Harari, G. M., Wang, R., Wang, W., Campbell, A. T., Mueller, S. R., ACM ASSOC COMPUTING MACHINERY. 2017: 57–60