Jeffrey Hancock
Harry and Norman Chandler Professor of Communication
Academic Appointments
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Professor, Communication
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Faculty Affiliate, Institute for Human-Centered Artificial Intelligence (HAI)
Program Affiliations
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Symbolic Systems Program
2020-21 Courses
- Advanced Studies in Behavior and Social Media
COMM 322 (Aut) - Introduction to Communication
COMM 1 (Aut) - Language and Technology
COMM 324 (Aut) - Truth, Trust, and Tech
COMM 124, COMM 224 (Win) -
Independent Studies (6)
- Advanced Individual Work
COMM 399 (Aut, Win, Spr, Sum) - Curriculum Practical Training
COMM 380 (Aut, Win, Spr, Sum) - Honors Thesis
COMM 195 (Aut, Win, Spr, Sum) - Individual Work
COMM 199 (Aut, Win, Spr, Sum) - Individual Work
COMM 299 (Aut, Win, Spr, Sum) - Media Studies M.A. Project
COMM 290 (Aut, Win, Spr)
- Advanced Individual Work
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Prior Year Courses
2019-20 Courses
- Advanced Studies in Behavior and Social Media
COMM 322 (Aut) - Introduction to Communication
COMM 1 (Aut) - Language and Technology
COMM 324 (Win) - Lies, Trust, and Tech
COMM 124, COMM 224 (Win)
2018-19 Courses
- Advanced Studies in Behavior and Social Media
COMM 322 (Win) - Introduction to Communication
COMM 1 (Aut) - Language and Technology
COMM 324 (Aut) - Lies, Trust, and Tech
COMM 124, COMM 224 (Win)
- Advanced Studies in Behavior and Social Media
Stanford Advisees
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Jordan Fox -
Doctoral Dissertation Reader (AC)
Samuel Chang, Dave Dixon, Anna Gibson, Jihye Lee, Dan Muise, Katie Roehrick -
Doctoral Dissertation Advisor (AC)
Mufan Luo -
Master's Program Advisor
Eleni Aneziris, Malik Antoine, Andrew Aprahamian, Daniella McMahon, Emma Morris, Libby Muir, Jennifer Park, Kathryn Rydberg, Anna Salamone, Sam Silverman, Anna Wilson -
Doctoral Dissertation Co-Advisor (AC)
D Metaxa -
Doctoral (Program)
Ross Dahlke, Sabrina Huang, Angela Lee, Mufan Luo, Hannah Mieczkowski, Ryan Moore
All Publications
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The Social Impact of Deepfakes
CYBERPSYCHOLOGY BEHAVIOR AND SOCIAL NETWORKING
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
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"Bringing you into the zoom": The power of authentic engagement in a time of crisis in the USA
JOURNAL OF CHILDREN AND MEDIA
2020
View details for DOI 10.1080/17482798.2020.1858437
View details for Web of Science ID 000599856600001
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Assessing Mental Health among College Students Using Mobile Apps: Acceptability and Feasibility
JOURNAL OF COLLEGE STUDENT PSYCHOTHERAPY
2020
View details for DOI 10.1080/87568225.2020.1842280
View details for Web of Science ID 000590764300001
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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
2020; 6 (4)
View details for DOI 10.1177/2056305120961784
View details for Web of Science ID 000595936900001
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The Deception Spiral: Corporate Obfuscation Leads to Perceptions of Immorality and Cheating Behavior
JOURNAL OF LANGUAGE AND SOCIAL PSYCHOLOGY
2020
View details for DOI 10.1177/0261927X20949594
View details for Web of Science ID 000560773900001
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Older Adults, Social Technologies, and the Coronavirus Pandemic: Challenges, Strengths, and Strategies for Support
SOCIAL MEDIA + SOCIETY
2020; 6 (3)
View details for DOI 10.1177/2056305120948162
View details for Web of Science ID 000561499300001
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The Outsourcing of Online Dating: Investigating the Lived Experiences of Online Dating Assistants Working in the Contemporary Gig Economy
SOCIAL MEDIA + SOCIETY
2020; 6 (3)
View details for DOI 10.1177/2056305120957290
View details for Web of Science ID 000576436800001
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Credibility Perceptions and Detection Accuracy of Fake News Headlines on Social Media: Effects of Truth-Bias and Endorsement Cues
COMMUNICATION RESEARCH
2020
View details for DOI 10.1177/0093650220921321
View details for Web of Science ID 000535024900001
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The Analysis of Nonverbal Communication: The Dangers of Pseudoscience in Security and Justice Contexts
ANUARIO DE PSICOLOGIA JURIDICA
2020; 30 (1): 1–12
View details for DOI 10.5093/apj2019a9
View details for Web of Science ID 000509344000001
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AI-Mediated Communication: Definition, Research Agenda, and Ethical Considerations
JOURNAL OF COMPUTER-MEDIATED COMMUNICATION
2020; 25 (1): 89–100
View details for DOI 10.1093/jcmc/zmz022
View details for Web of Science ID 000569052500008
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Context in a bottle: Language-action cues in spontaneous computer mediated deception
COMPUTERS IN HUMAN BEHAVIOR
2019; 91: 33–41
View details for DOI 10.1016/j.chb.2018.09.008
View details for Web of Science ID 000452939300005
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Evaluation of a Mobile Device Survey System for Behavioral Risk Factors (SHAPE): App Development and Usability Study.
JMIR formative research
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
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Helping Not Hurting: Applying the Stereotype Content Model and BIAS Map to Social Robotics
IEEE. 2019: 222–29
View details for Web of Science ID 000467295400029
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Psychological and physiological effects of applying self-control to the mobile phone.
PloS one
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
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Self-disclosure and social media: motivations, mechanisms and psychological well-being.
Current opinion in psychology
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
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AI-Mediated Communication: How the Perception that Profile Text was Written by AI Affects Trustworthiness
ASSOC COMPUTING MACHINERY. 2019
View details for DOI 10.1145/3290605.3300469
View details for Web of Science ID 000474467903010
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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
2018; 45 (8): 1167–92
View details for DOI 10.1177/0093650216631094
View details for Web of Science ID 000450335100004
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Deception in Mobile Dating Conversations
JOURNAL OF COMMUNICATION
2018; 68 (3): 547–69
View details for DOI 10.1093/joc/jqy019
View details for Web of Science ID 000449503100011
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Psychopaths Online: The Linguistic Traces of Psychopathy in Email, Text Messaging and Facebook
MEDIA AND COMMUNICATION
2018; 6 (3): 83–92
View details for DOI 10.17645/mac.v6i3.1499
View details for Web of Science ID 000449673900005
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Fake News in the News: An Analysis of Partisan Coverage of the Fake News Phenomenon
ASSOC COMPUTING MACHINERY. 2018: 289–92
View details for DOI 10.1145/3272973.3274079
View details for Web of Science ID 000482113000073
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Ethical Dilemma: Deception Dynamics in Computer-Mediated Group Communication
JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY
2017; 68 (12): 2729–42
View details for DOI 10.1002/asi.23849
View details for Web of Science ID 000414718000004
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How Advertorials Deactivate Advertising Schema: MTurk-Based Experiments to Examine Persuasion Tactics and Outcomes in Health Advertisements
COMMUNICATION RESEARCH
2017; 44 (7): 1019–45
View details for DOI 10.1177/0093650216644017
View details for Web of Science ID 000422777300005
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Scaling Up Research on Drug Abuse and Addiction Through Social Media Big Data
JOURNAL OF MEDICAL INTERNET RESEARCH
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