Jeffrey Hancock

All Publications

• The Social Impact of Deepfakes CYBERPSYCHOLOGY BEHAVIOR AND SOCIAL NETWORKING Hancock, J. T., Bailenson, J. N. 2021; 24 (3): 149–52

  View details for DOI 10.1089/cyber.2021.29208.jth

  View details for Web of Science ID 000632152700002

  View details for PubMedID 33760669

• "Bringing you into the zoom": The power of authentic engagement in a time of crisis in the USA JOURNAL OF CHILDREN AND MEDIA Lee, A. Y., Moskowitz-Sweet, G., Pelavin, E., Rivera, O., Hancock, J. T. 2020

  View details for DOI 10.1080/17482798.2020.1858437

  View details for Web of Science ID 000599856600001

• Assessing Mental Health among College Students Using Mobile Apps: Acceptability and Feasibility JOURNAL OF COLLEGE STUDENT PSYCHOTHERAPY Palesh, O., Oakley-Girvan, I., Richardson, A., Nelson, L. M., Clark, R., Hancock, J., Acle, C., Lavista, J. M., Miller, Y., Gore-Felton, C. 2020

  View details for DOI 10.1080/87568225.2020.1842280

  View details for Web of Science ID 000590764300001

• Priming Effects of Social Media Use Scales on Well-Being Outcomes: The Influence of Intensity and Addiction Scales on Self-Reported Depression SOCIAL MEDIA + SOCIETY Mieczkowski, H., Lee, A. Y., Hancock, J. T. 2020; 6 (4)

  View details for DOI 10.1177/2056305120961784

  View details for Web of Science ID 000595936900001

• The Deception Spiral: Corporate Obfuscation Leads to Perceptions of Immorality and Cheating Behavior JOURNAL OF LANGUAGE AND SOCIAL PSYCHOLOGY Markowitz, D. M., Kouchaki, M., Hancock, J. T., Gino, F. 2020

  View details for DOI 10.1177/0261927X20949594

  View details for Web of Science ID 000560773900001

• Older Adults, Social Technologies, and the Coronavirus Pandemic: Challenges, Strengths, and Strategies for Support SOCIAL MEDIA + SOCIETY Moore, R. C., Hancock, J. T. 2020; 6 (3)

  View details for DOI 10.1177/2056305120948162

  View details for Web of Science ID 000561499300001

• The Outsourcing of Online Dating: Investigating the Lived Experiences of Online Dating Assistants Working in the Contemporary Gig Economy SOCIAL MEDIA + SOCIETY Rochadiat, A. P., Tong, S., Hancock, J. T., Stuart-Ulin, C. 2020; 6 (3)

  View details for DOI 10.1177/2056305120957290

  View details for Web of Science ID 000576436800001

• Credibility Perceptions and Detection Accuracy of Fake News Headlines on Social Media: Effects of Truth-Bias and Endorsement Cues COMMUNICATION RESEARCH Luo, M., Hancock, J. T., Markowitz, D. M. 2020

  View details for DOI 10.1177/0093650220921321

  View details for Web of Science ID 000535024900001

• The Analysis of Nonverbal Communication: The Dangers of Pseudoscience in Security and Justice Contexts ANUARIO DE PSICOLOGIA JURIDICA Denault, V., Plusquellec, P., Jupe, L. M., St-Yves, M., Dunbar, N. E., Hartwig, M., Sporer, S. L., Rioux-Turcotte, J., Jarry, J., Walsh, D., Otgaar, H., Viziteu, A., Talwar, V., Keatley, D. A., Blandon-Gitlin, I., Townson, C., Deslauriers-Varin, N., Lilienfeld, S. O., Patterson, M. L., Areh, I., Allan, A., Cameron, H., Boivin, R., ten Brinke, L., Masip, J., Bull, R., Cyr, M., Hope, L., Stromwall, L. A., Bennett, S. J., Al Menaiya, F., Leo, R. A., Vredeveldt, A., Laforest, M., Honts, C. R., Manzanero, A. L., Mann, S., Granhag, P., Ask, K., Gabbert, F., Guay, J., Coutant, A., Hancock, J., Manusov, V., Burgoon, J. K., Kleinman, S. M., Wright, G., Landstrom, S., Freckelton, I., Vernham, Z., van Koppen, P. J. 2020; 30 (1): 1–12

  View details for DOI 10.5093/apj2019a9

  View details for Web of Science ID 000509344000001

• AI-Mediated Communication: Definition, Research Agenda, and Ethical Considerations JOURNAL OF COMPUTER-MEDIATED COMMUNICATION Hancock, J. T., Naaman, M., Levy, K. 2020; 25 (1): 89–100

  View details for DOI 10.1093/jcmc/zmz022

  View details for Web of Science ID 000569052500008

• Context in a bottle: Language-action cues in spontaneous computer mediated deception COMPUTERS IN HUMAN BEHAVIOR Ho, S., Hancock, J. T. 2019; 91: 33–41

  View details for DOI 10.1016/j.chb.2018.09.008

  View details for Web of Science ID 000452939300005

• Evaluation of a Mobile Device Survey System for Behavioral Risk Factors (SHAPE): App Development and Usability Study. JMIR formative research Oakley-Girvan, I., Lavista, J. M., Miller, Y., Davis, S., Acle, C., Hancock, J., Nelson, L. M. 2019; 3 (1): e10246

  Abstract

  BACKGROUND: Risk factors, including limited exercise, poor sleep, smoking, and alcohol and drug use, if mitigated early, can improve long-term health. Risk prevalence has traditionally been measured using methods that now have diminished participation rates. With >75% of American citizens owning smartphones, new data collection methods using mobile apps can be evaluated.OBJECTIVE: The objective of our study was to describe the development, implementation, and evaluation of a mobile device-based survey system for behavioral risk assessment. Specifically, we evaluated its feasibility, usability, acceptability, and validity.METHODS: We enrolled 536 students from 3 Vermont State Colleges. Iterative mobile app development incorporated focus groups, extensive testing, and the following 4 app versions: iOS standard, iOS gamified, Android standard, and Android gamified. We aimed to capture survey data, paradata, and ambient data such as geolocation. Using 3 separate surveys, we asked a total of 27 questions that included demographic characteristics, behavioral health, and questions regarding the app's usability and survey process.RESULTS: Planned enrollment was exceeded in just a few days. There were 1392 "hits" to the landing page where the app could be downloaded. Excluding known project testers and others not part of the study population, 670 participants downloadeded the SHAPE app. Of those, 94.9% of participants (636/670) agreed to participate by providing in-app consent. Of the 636 who provided consent, 84.3% (536/636) were deemed eligible for the study. The majority of eligible respondents completed the initial survey (459/536, 85.6%), whereas 29.9% (160/536) completed the second survey and 28.5% (153/536) completed the third survey. The SHAPE survey obtained 414 participants on the behavioral risk items in survey 1, which is nearly double the 209 participants who completed the traditional Vermont College Health Survey in 2014. SHAPE survey responses were consistent with the traditionally collected Vermont College Health Survey data.CONCLUSIONS: This study provides data highlighting the potential for mobile apps to improve population-based health, including an assessment of recruitment methods, burden and response rapidity, and future adaptations. Although gamification and monetary rewards were relatively unimportant to this study population, item response theory may be technologically feasible to reduce individual survey burden. Additional data collected by smartphones, such as geolocation, could be important in additional analysis, such as neighborhood characteristics and their impact on behavioral risk factors. Mobile tools that offer rapid adaptation for specific populations may improve research data collection for primary prevention and could be used to improve engagement and health outcomes.

  View details for PubMedID 30684441

• AI-Mediated Communication: How the Perception that Profile Text was Written by AI Affects Trustworthiness Jakesch, M., French, M., Ma, X., Hancock, J. T., Naaman, M., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2019

  View details for DOI 10.1145/3290605.3300469

  View details for Web of Science ID 000474467903010

• Self-disclosure and social media: motivations, mechanisms and psychological well-being. Current opinion in psychology Luo, M. n., Hancock, J. T. 2019; 31: 110–15

  Abstract

  Self-disclosure is pervasive on social media and has significant implications for psychological well-being. In this review we synthesize recent research on the motivations, mechanisms and effects of self-disclosure on well-being and then propose a framework that highlights the bidirectional relationship between self-disclosure and well-being. The framework details the mechanisms by which self-disclosure on social media can influence well-being and how self-disclosure fulfills particular needs of individuals with different well-being characteristics. We call for future research to examine the proposed bi-directional relationship, especially studies designed to tease out causal effects.

  View details for DOI 10.1016/j.copsyc.2019.08.019

  View details for PubMedID 31563107

• Psychological and physiological effects of applying self-control to the mobile phone. PloS one Markowitz, D. M., Hancock, J. T., Bailenson, J. N., Reeves, B. n. 2019; 14 (11): e0224464

  Abstract

  This preregistered study examined the psychological and physiological consequences of exercising self-control with the mobile phone. A total of 125 participants were randomly assigned to sit in an unadorned room for six minutes and either (a) use their mobile phone, (b) sit alone with no phone, or (c) sit with their device but resist using it. Consistent with prior work, participants self-reported more concentration difficulty and more mind wandering with no device present compared to using the phone. Resisting the phone led to greater perceived concentration abilities than sitting without the device (not having external stimulation). Failing to replicate prior work, however, participants without external stimulation did not rate the experience as less enjoyable or more boring than having something to do. We also observed that skin conductance data were consistent across conditions for the first three-minutes of the experiment, after which participants who resisted the phone were less aroused than those who were without the phone. We discuss how the findings contribute to our understanding of exercising self-control with mobile media and how psychological consequences, such as increased mind wandering and focusing challenges, relate to periods of idleness or free thinking.

  View details for DOI 10.1371/journal.pone.0224464

  View details for PubMedID 31682619

• Helping Not Hurting: Applying the Stereotype Content Model and BIAS Map to Social Robotics Mieczkowski, H., Liu, S., Hancock, J., Reeves, B., IEEE IEEE. 2019: 222–29

  View details for Web of Science ID 000467295400029

• Lies in the Eye of the Beholder: Asymmetric Beliefs about One's Own and Others' Deceptiveness in Mediated and Face-to-Face Communication COMMUNICATION RESEARCH Toma, C. L., Jiang, L., Hancock, J. T. 2018; 45 (8): 1167–92

  View details for DOI 10.1177/0093650216631094

  View details for Web of Science ID 000450335100004

• Deception in Mobile Dating Conversations JOURNAL OF COMMUNICATION Markowitz, D. M., Hancock, J. T. 2018; 68 (3): 547–69

  View details for DOI 10.1093/joc/jqy019

  View details for Web of Science ID 000449503100011

• Fake News in the News: An Analysis of Partisan Coverage of the Fake News Phenomenon Che, X., Metaxa-Kakavouli, D., Hancock, J. T., ACM ASSOC COMPUTING MACHINERY. 2018: 289–92

  View details for DOI 10.1145/3272973.3274079

  View details for Web of Science ID 000482113000073

• Psychopaths Online: The Linguistic Traces of Psychopathy in Email, Text Messaging and Facebook MEDIA AND COMMUNICATION Hancock, J. T., Woodworth, M., Boochever, R. 2018; 6 (3): 83–92

  View details for DOI 10.17645/mac.v6i3.1499

  View details for Web of Science ID 000449673900005

• Ethical Dilemma: Deception Dynamics in Computer-Mediated Group Communication JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY Ho, S., Hancock, J. T., Booth, C. 2017; 68 (12): 2729–42

  View details for DOI 10.1002/asi.23849

  View details for Web of Science ID 000414718000004

• Scaling Up Research on Drug Abuse and Addiction Through Social Media Big Data JOURNAL OF MEDICAL INTERNET RESEARCH Kim, S., Marsch, L. A., Hancock, J. T., Das, A. K. 2017; 19 (10): e353

  Abstract

  Substance use-related communication for drug use promotion and its prevention is widely prevalent on social media. Social media big data involve naturally occurring communication phenomena that are observable through social media platforms, which can be used in computational or scalable solutions to generate data-driven inferences. Despite the promising potential to utilize social media big data to monitor and treat substance use problems, the characteristics, mechanisms, and outcomes of substance use-related communications on social media are largely unknown. Understanding these aspects can help researchers effectively leverage social media big data and platforms for observation and health communication outreach for people with substance use problems.The objective of this critical review was to determine how social media big data can be used to understand communication and behavioral patterns of problematic use of prescription drugs. We elaborate on theoretical applications, ethical challenges and methodological considerations when using social media big data for research on drug abuse and addiction. Based on a critical review process, we propose a typology with key initiatives to address the knowledge gap in the use of social media for research on prescription drug abuse and addiction.First, we provided a narrative summary of the literature on drug use-related communication on social media. We also examined ethical considerations in the research processes of (1) social media big data mining, (2) subgroup or follow-up investigation, and (3) dissemination of social media data-driven findings. To develop a critical review-based typology, we searched the PubMed database and the entire e-collection theme of "infodemiology and infoveillance" in the Journal of Medical Internet Research / JMIR Publications. Studies that met our inclusion criteria (eg, use of social media data concerning non-medical use of prescription drugs, data informatics-driven findings) were reviewed for knowledge synthesis. User characteristics, communication characteristics, mechanisms and predictors of such communications, and the psychological and behavioral outcomes of social media use for problematic drug use-related communications are the dimensions of our typology. In addition to ethical practices and considerations, we also reviewed the methodological and computational approaches used in each study to develop our typology.We developed a typology to better understand non-medical, problematic use of prescription drugs through the lens of social media big data. Highly relevant studies that met our inclusion criteria were reviewed for knowledge synthesis. The characteristics of users who shared problematic substance use-related communications on social media were reported by general group terms, such as adolescents, Twitter users, and Instagram users. All reviewed studies examined the communication characteristics, such as linguistic properties, and social networks of problematic drug use-related communications on social media. The mechanisms and predictors of such social media communications were not directly examined or empirically identified in the reviewed studies. The psychological or behavioral consequence (eg, increased behavioral intention for mimicking risky health behaviors) of engaging with and being exposed to social media communications regarding problematic drug use was another area of research that has been understudied.We offer theoretical applications, ethical considerations, and empirical evidence within the scope of social media communication and prescription drug abuse and addiction. Our critical review suggests that social media big data can be a tremendous resource to understand, monitor and intervene on drug abuse and addiction problems.

  View details for PubMedID 29089287

• How Advertorials Deactivate Advertising Schema: MTurk-Based Experiments to Examine Persuasion Tactics and Outcomes in Health Advertisements COMMUNICATION RESEARCH Kim, S., Hancock, J. T. 2017; 44 (7): 1019–45

  View details for DOI 10.1177/0093650216644017

  View details for Web of Science ID 000422777300005