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2022-23 Courses


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  • Effects of Using Artificial Intelligence on Interpersonal Perceptions of Job Applicants. Cyberpsychology, behavior and social networking Weiss, D., Liu, S. X., Mieczkowski, H., Hancock, J. T. 1800

    Abstract

    Text-based artificial intelligence (AI) systems are increasingly integrated into a host of interpersonal domains. Although decision-making and person perception in hiring and employment opportunities have been an area of psychological interest for many years, only recently have scholars begun to investigate the role that AI plays in this context. To better understand the impact of AI in employment-related contexts, we conducted two experiments investigating how the use of AI by applicants influences their job opportunities. In our preregistered Study 1, we examined how a prospective job applicants' use of AI, as well as their language status (native English speaker or non-native English speaker), influenced participants' impressions of their warmth, competence, social attractiveness, and hiring desirability. In Study 2, we examined how receiving assistance impacted interpersonal perceptions, and how perceptions might change whether the help was provided by AI or by another human. The results from both experiments suggest that the use of AI technologies can negatively influence perceptions of jobseekers. This negative impact may be grounded in the perception of receiving any type of help, whether it be from a machine or a person. These studies provide additional evidence for the Computers as Social Actors framework and advance our understanding of AI-Mediated Communication. The results also raise questions about transparency and deception related to AI use in interpersonal contexts.

    View details for DOI 10.1089/cyber.2020.0863

    View details for PubMedID 35021895

  • The Truth Project JOURNAL OF LANGUAGE AND SOCIAL PSYCHOLOGY Markowitz, D. M., Blackburn, K. G., Saxena, K., Marion, J., Olivarez, O., Hernandez, R., Woodworth, M. T., Hancock, J. T. 2021
  • Will You Go on a Date with Me? Predicting First Dates from Linguistic Traces in Online Dating Messages JOURNAL OF LANGUAGE AND SOCIAL PSYCHOLOGY Huang, S. A., Hancock, J. T. 2021
  • Not All AI are Equal: Exploring the Accessibility of AI-Mediated Communication Technology COMPUTERS IN HUMAN BEHAVIOR Goldenthal, E., Park, J., Liu, S. X., Mieczkowski, H., Hancock, J. T. 2021; 125
  • An Explication of Identity Shift Theory Getting Our Shift Together JOURNAL OF MEDIA PSYCHOLOGY-THEORIES METHODS AND APPLICATIONS Carr, C. T., Kim, Y., Valov, J. J., Rosenbaum, J. E., Johnson, B. K., Hancock, J. T., Gonzales, A. L. 2021; 33 (4): 202-214
  • The Role of Subjective Construals on Reporting and Reasoning about Social Media Use SOCIAL MEDIA + SOCIETY Lee, A. Y., Katz, R., Hancock, J. 2021; 7 (3)
  • Age-Related Differences in Experiences with Social Distancing at the Onset of the COVID-19 Pandemic: A Computational and Content Analytic Investigation of Natural Language. JMIR human factors Moore, R. C., Lee, A. Y., Hancock, J. T., Halley, M. C., Linos, E. 2021

    Abstract

    BACKGROUND: As COVID-19 poses different levels of threat to people of different ages, health communication regarding prevention measures such as social distancing and isolation may be strengthened by understanding the unique experiences of different age groups.OBJECTIVE: The aim was to examine how people of different ages (1) experienced the impact of the COVID-19 pandemic and (2) their respective rates and reasons for compliance or non-compliance with social distancing and isolation health guidance.METHODS: We fielded a survey on social media (N = 17,287) early in the pandemic to examine the emotional impact of COVID-19 and individuals' rates and reasons for non-compliance with public health guidance, using computational and content analytic methods of linguistic analysis. The majority of our participants (76.5%) were from the United States.RESULTS: Younger (18-31), middle-aged (32-44, 45-64), and older (65+) individuals significantly varied in how they described the impact of COVID-19 on their lives, including their emotional experience, self-focused attention, and topical concerns. Younger individuals were more emotionally negative and self-focused, while middle-aged people were other-focused and concerned with family. The oldest and most at-risk group was most concerned with health-related terms but were also lower in anxiety and higher in the use of emotionally positive terms than the other, less at-risk age groups. While all groups discussed topics such as acquiring essential supplies, they differentially experienced the impact of school closures and limited social interactions. We also found relatively high rates of non-compliance with COVID-19 prevention measures, such as social distancing and self-isolation, with younger people being more likely to be non-compliant than older people, (P < .001). Among the 43% of respondents who did not fully comply with health orders, people differed substantially in the reasons they gave for non-compliance. The most common reason for non-compliance was not being able to afford missing work (57.3%). While work obligations proved challenging for participants across ages, younger people struggled more to find adequate space to self-isolate and manage their mental and physical health; middle-aged people faced more concerns regarding childcare; and older people perceived themselves as able to take sufficient precautions.CONCLUSIONS: Analysis of natural language can provide insight into rapidly developing public health challenges like the COVID-19 pandemic, uncovering individual differences in emotional experiences and health-related behaviors. In this case, our analyses revealed significant differences between different age groups in feelings about and responses to public health orders aimed to mitigate the spread of COVID-19. To improve public compliance with health orders as the pandemic continues, health communication strategies could be made more effective by being tailored to these age-related differences.CLINICALTRIAL:

    View details for DOI 10.2196/26043

    View details for PubMedID 33914689

  • 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

  • Identifying Silver Linings During the Pandemic Through Natural Language Processing. Frontiers in psychology Lossio-Ventura, J. A., Lee, A. Y., Hancock, J. T., Linos, N., Linos, E. 2021; 12: 712111

    Abstract

    COVID-19 has presented an unprecedented challenge to human welfare. Indeed, we have witnessed people experiencing a rise of depression, acute stress disorder, and worsening levels of subclinical psychological distress. Finding ways to support individuals' mental health has been particularly difficult during this pandemic. An opportunity for intervention to protect individuals' health & well-being is to identify the existing sources of consolation and hope that have helped people persevere through the early days of the pandemic. In this paper, we identified positive aspects, or "silver linings," that people experienced during the COVID-19 crisis using computational natural language processing methods and qualitative thematic content analysis. These silver linings revealed sources of strength that included finding a sense of community, closeness, gratitude, and a belief that the pandemic may spur positive social change. People's abilities to engage in benefit-finding and leverage protective factors can be bolstered and reinforced by public health policy to improve society's resilience to the distress of this pandemic and potential future health crises.

    View details for DOI 10.3389/fpsyg.2021.712111

    View details for PubMedID 34539512

  • "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
  • 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
  • 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)
  • 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
  • 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)
  • 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)
  • 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
  • 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
  • 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
  • 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

  • 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

  • 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

  • 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
  • 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
  • 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
  • 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

  • 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
  • Computer-Mediated Deception: Collective Language-Action Cues as Stigmergic Signals for Computational Intelligence Ho, S., Hancock, J. T., Bui, T. X. HICSS. 2018: 1671-1680
  • 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
  • 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
  • Your post is embarrassing me: Face threats, identity, and the audience on Facebook COMPUTERS IN HUMAN BEHAVIOR Oeldorf-Hirsch, A., Birnholtz, J., Hancock, J. T. 2017; 73: 92-99
  • Should I Share That? Prompting Social Norms That Influence Privacy Behaviors on a Social Networking Site JOURNAL OF COMPUTER-MEDIATED COMMUNICATION Spottswood, E. L., Hancock, J. T. 2017; 22 (2): 55-70

    View details for DOI 10.1111/jcc4.12182

    View details for Web of Science ID 000397094200001

  • Self-Disclosure and Perceived Trustworthiness of Airbnb Host Profiles Ma, X., Hancock, J. T., Mingjie, K., Naaman, M., Assoc Comp Machinery ASSOC COMPUTING MACHINERY. 2017: 2397-2409
  • Linguistic analysis of chat transcripts from child predator undercover sex stings JOURNAL OF FORENSIC PSYCHIATRY & PSYCHOLOGY Drouin, M., Boyd, R. L., Hancock, J. T., James, A. 2017; 28 (4): 437-457
  • The 27 Club: Music Lyrics Reflect Psychological Distress COMMUNICATION REPORTS Markowitz, D. M., Hancock, J. T. 2017; 30 (1): 1-13
  • The positivity bias and prosocial deception on facebook COMPUTERS IN HUMAN BEHAVIOR Spottswood, E. L., Hancock, J. T. 2016; 65: 252-259
  • Online dating system design and relational decision making: Choice, algorithms, and control PERSONAL RELATIONSHIPS Tong, S. T., Hancock, J. T., Slatcher, R. B. 2016; 23 (4): 645-662

    View details for DOI 10.1111/pere.12158

    View details for Web of Science ID 000390564800002

  • Linguistic Obfuscation in Fraudulent Science JOURNAL OF LANGUAGE AND SOCIAL PSYCHOLOGY Markowitz, D. M., Hancock, J. T. 2016; 35 (4): 435-445
  • Computer-Mediated Deception: Strategies Revealed by Language-Action Cues in Spontaneous Communication JOURNAL OF MANAGEMENT INFORMATION SYSTEMS Ho, S. M., Hancock, J. T., Booth, C., Liu, X. 2016; 33 (2): 393-420
  • Effects of Network Connections on Deception and Halo Effects in Linkedin PSYCHOLOGY OF SOCIAL NETWORKING: PERSONAL EXPERIENCE IN ONLINE COMMUNITIES Guillory, J. E., Hancock, J. T., Riva, G., Wiederhold, B. K., Cipresso, P. 2016: 66-77
  • The Influence of Technology on Romantic Relationships: Understanding Online Dating Tong, S., Hancock, J. T., Slatcher, R. B., Meiselwitz, G. SPRINGER INTERNATIONAL PUBLISHING AG. 2016: 162-173
  • Demystifying Insider Threat: Language-Action Cues in Group Dynamics Ho, S., Hancock, J. T., Booth, C., Burmester, M., Liu, X., Timmarajus, S. S., Bui, T. X., Sprague, R. H. IEEE COMPUTER SOC. 2016: 2729-2738
  • Real or Spiel? A Decision Tree Approach for Automated Detection of Deceptive Language-Action Cues Ho, S., Hancock, J. T., Booth, C., Liu, X., Liu, M., Timmarajus, S. S., Burmester, M., Bui, T. X., Sprague, R. H. IEEE COMPUTER SOC. 2016: 3706-3715