Book contents
- The Cambridge Handbook of Cyber Behavior
- The Cambridge Handbook of Cyber Behavior
- Copyright page
- Contents
- Figures
- Tables
- Contributors
- Preface
- Part I Users in Cyber Behavior
- Part II Technologies in Cyber Behavior
- Part III Activities in Cyber Behavior
- Part IV Effects in Cyber Behavior
- 30 Video Game Effects
- 31 Serious Games in Mental Health Treatment
- 32 Gaming Disorder
- 33 Problematic Mobile Phone Use
- 34 Interventions for Addictive Behaviors in Cyberspace
- 35 Electronic Aggression
- 36 Cyberbullying in Twenty-First-Century Schools
- 37 Hate Speech and Adolescents
- 38 Cyber Racism
- 39 Cyberdeception
- Index
- References
39 - Cyberdeception
from Part IV - Effects in Cyber Behavior
Published online by Cambridge University Press: 06 December 2024
Edited by
Book contents
- The Cambridge Handbook of Cyber Behavior
- The Cambridge Handbook of Cyber Behavior
- Copyright page
- Contents
- Figures
- Tables
- Contributors
- Preface
- Part I Users in Cyber Behavior
- Part II Technologies in Cyber Behavior
- Part III Activities in Cyber Behavior
- Part IV Effects in Cyber Behavior
- 30 Video Game Effects
- 31 Serious Games in Mental Health Treatment
- 32 Gaming Disorder
- 33 Problematic Mobile Phone Use
- 34 Interventions for Addictive Behaviors in Cyberspace
- 35 Electronic Aggression
- 36 Cyberbullying in Twenty-First-Century Schools
- 37 Hate Speech and Adolescents
- 38 Cyber Racism
- 39 Cyberdeception
- Index
- References
Summary
1 Introduction
2 A Review of Deception Constructs
3 Cyberdeception Frameworks
4 Cyberdeception Perpetrators and Their Motives
5 Manifestations of Cyberdeception
5.1 False Health Information
5.2 Fake News
5.3 Online Scams
5.4 Online Dating
5.5 Online Assessment
5.6 Other Cyberdeception Manifestations
6 Cyberdeception Detection
6.1 Human-Based Cyberdeception Detection
6.2 Computer-Based Cyberdeception Detection
7 Promising Avenues for Cyberdeception Research
8 Conclusion
Keywords
- Type
- Chapter
- Information
- The Cambridge Handbook of Cyber Behavior , pp. 1156 - 1205Publisher: Cambridge University PressPrint publication year: 2023
References
AARP. (June, 2020). Health fraud. AARP. Retrieved from www.aarp.org/money/scams-fraud/info-2020/health-miracle-cures.htmlGoogle Scholar
Agrawal, A., Catalini, C., & Goldfarb, A. (2014). Some simple economics of crowdfunding. Innovation Policy and the Economy, 14(1), 63–97.CrossRefGoogle Scholar
Ahler, D. J., Roush, C. E., & Sood, G. (2020, July). The micro-task market for lemons: Data quality on Amazon’s Mechanical Turk. In Meeting of the Midwest Political Science Association (pp. 1–67).CrossRefGoogle Scholar
Ajzen, I. (1991). Theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179–211.CrossRefGoogle Scholar
Allcott, H., & Gentzkow, M. (2017). Social media and fake news in the 2016 election. Journal of Economic Perspectives, 31(2), 211–236.CrossRefGoogle Scholar
Allington, D., Duffy, B., Wessely, S., Dhavan, N., & Rubin, J. (2020). Health-protective behaviour, social media usage and conspiracy belief during the COVID-19 public health emergency. Psychological Medicine, 51(10), 1763–1769.CrossRefGoogle ScholarPubMed
Anderson, A., Bryce, J., Ireland, C. A., & Ireland, J. L. (2019). A preliminary review of cyber-detection factors: Offering from a systematic review. Salus: An International Journal of Law Enforcement and Public Safety, 7(1), 88–107.Google Scholar
Anderson, M., Vogels, E. A., & Turner, E. (2020, February). The virtues and downsides of online dating. Pew Research Center. Retrieved from www.pewresearch.org/internet/2020/02/06/the-virtues-and-downsides-of-online-dating/Google Scholar
Anthony, A., & Moulding, R. (2019). Breaking the news: Belief in fake news and conspiracist beliefs. Australian Journal of Psychology, 71(2), 154–162.CrossRefGoogle Scholar
Apuke, O. D., & Omar, B. (2021). Fake news and COVID-19: modelling the predictors of fake news sharing among social media users. Telematics and Informatics, 56, 101475.CrossRefGoogle Scholar
Arrouas, M. (2014, March). Do you think the CIA infected African Americans with HIV? You’re not alone. TIME. Retrieved from https://time.com/29810/half-of-americans-believe-in-medical-conspiracy-theories/Google Scholar
Arthur, W. Jr, Glaze, R. M., Villado, A. J., & Taylor, J. E. (2010). The magnitude and extent of cheating and response distortion effects on unproctored internet‐based tests of cognitive ability and personality. International Journal of Selection and Assessment, 18(1), 1–16.CrossRefGoogle Scholar
Ashuta. (2017, October 6). You won’t believe how these 9 shocking clickbaits work! (number 8 is a killer!). Medium. Retrieved from https://medium.com/zerone-magazine/you-wont-believe-how-these-9-shocking-clickbaits-work-number-8-is-a-killer-4cb2ceded8b6Google Scholar
Axt, J. R., Landau, M. J., Kay, & A. C. (2020). The psychological appeal of fake news attributions. Psychological Science, 31(7), 848–857.CrossRefGoogle ScholarPubMed
Bago, B., Rand, D. G., & Pennycook, G. (2020). Fake news, fast and slow: Deliberation reduces belief in false (but not true) news headlines. Journal of Experimental Psychology: General, 149(8), 1608–1613.CrossRefGoogle ScholarPubMed
Bargh, J. A., McKenna, K. Y., & Fitzsimons, G. M. (2002). Can you see the real me? Activation and expression of the “true self” on the Internet. Journal of Social Issues, 58(1), 33–48.CrossRefGoogle Scholar
Barrick, M. R., & Mount, M. K. (1996). Effects of impression management and self-deception on the predictive validity of personality constructs. Journal of Applied Psychology, 81, 261–272.CrossRefGoogle ScholarPubMed
Beck, V. (2014). Testing a model to predict online cheating – Much ado about nothing. Active Learning in Higher Education, 15(1), 65–75.CrossRefGoogle Scholar
Beckmann, J., & Heckhausen, H. (2018). Motivation as a function of expectancy and incentive. In Heckhausen, J. & Heckhausen, H. (Eds), Motivation and Action (pp. 163–220). Springer, Cham.CrossRefGoogle Scholar
Berman, J., & Bruckman, A. S. (2001). The Turing Game: Exploring identity in an online environment. Convergence, 7(3), 83–102.CrossRefGoogle Scholar
Berners-Lee, T., & Fischetti, M. (1999). Weaving the web: The original design and ultimate destiny of the world wide web by its inventor. HarperCollins.Google Scholar
Betsch, C. (2017). Advocating for vaccination in a climate of science denial. Nature Microbiology, 2(7), 1–3.CrossRefGoogle Scholar
Binet, A. (1896). Psychology of prestidigitation. In Annual Report of the Board of Regents of the Smithsonian Institution (pp. 555–571). GPO.Google Scholar
Boitshwarelo, B., Reedy, A. K., & Billany, T. (2017). Envisioning the use of online tests in assessing twenty-first century learning: A literature review. Research and Practice in Technology Enhanced Learning, 12, 1–16.CrossRefGoogle ScholarPubMed
Boshmaf, Y., Muslukhov, I., Beznosov, K., & Ripeanu, M. (2011, December). The socialbot network: When bots socialize for fame and money. In Proceedings of the 27th Annual Computer Security Applications Conference (pp. 93–102). Association for Computing Machinery.CrossRefGoogle Scholar
Bouma, H. (1992). Gerontechnology: Making technology relevant for the elderly. In Bouma, H. & Graafmans, J. A. M. (Eds.), Gerontechnology (pp. 1–5). IOS Press.Google Scholar
Braithwaite, J. (1989). Crime, shame and reintegration. Cambridge University Press.CrossRefGoogle Scholar
Bronstein, M. V., Pennycook, G., Bear, A., Rand, D. G., & Cannon, T. D. (2019). Belief in fake news is associated with delusionality, dogmatism, religious fundamentalism, and reduced analytic thinking. Journal of Applied Research in Memory and Cognition, 8(1), 108–117.CrossRefGoogle Scholar
Brownell, S. E., Price, J. V., & Steinman, L. (2013). Science communication to the general public: Why we need to teach undergraduate and graduate students this skill as part of their formal scientific training. Journal of Undergraduate Neuroscience Education, 12, E6–E10.Google Scholar
Buchanan, T., & Whitty, M. T. (2014). The online dating romance scam: Causes and consequences of victimhood. Psychology, Crime & Law, 20(3), 261–283.CrossRefGoogle Scholar
Buckels, E. E., Trapnell, P. D., & Paulhus, D. L. (2014). Trolls just want to have fun. Personality and Individual Differences, 67, 97–102.CrossRefGoogle Scholar
Buhrmester, M., Kwang, T., & Gosling, S. D. (2011). Amazon’s Mechanical Turk: A new source of inexpensive, yet high-quality data? Perspectives on Psychological Science, 6, 3–5.CrossRefGoogle Scholar
Buller, D. B., & Burgoon, J. K. (1996). Interpersonal deception theory. Communication Theory, 6(3), 203–242.CrossRefGoogle Scholar
Camden, C., Motley, M. T., & Wilson, A. (1984). White lies in interpersonal communication: A taxonomy and preliminary investigation of social motivations. Western Journal of Speech Communication, 48(4), 309–325.CrossRefGoogle Scholar
Campan, A., Cuzzocrea, A., & Truta, T. M. (2017). Fighting fake news spread in online social networks: Actual trends and future research directions. In 2017 IEEE International Conference on Big Data (pp. 4453–4457).CrossRefGoogle Scholar
Campbell, C., & Grimm, P. E. (2019). The challenges native advertising poses: Exploring potential federal trade commission responses and identifying research needs. Journal of Public Policy & Marketing, 38(1), 110–123.CrossRefGoogle Scholar
Carlson, J. R., Carlson, D. S., & Ferguson, M. (2011). Deceptive impression management: Does deception pay in established workplace relationships? Journal of Business Ethics, 100(3), 497–514.CrossRefGoogle Scholar
Carlson, J. R., & George, J. F. (2004). Media appropriateness in the conduct and discovery of deceptive communication: The relative influence of richness and synchronicity. Group Decision and Negotiation, 13(2), 191–210.CrossRefGoogle Scholar
Carlson, J. R., George, J. F., Burgoon, J. K., Adkins, M., & White, C. H. (2004). Deception in computer-mediated communication. Group Decision and Negotiation, 13(1), 5–28.CrossRefGoogle Scholar
Caspi, A., & Gorsky, P. (2006). Online deception: Prevalence, motivation, and emotion. CyberPsychology & Behavior, 9(1), 54–59.CrossRefGoogle ScholarPubMed
Centers for Disease Control and Prevention. (2019, August). Making the vaccine decision: Addressing common concerns. Centers for Disease Control and Prevention. Retrieved from www.cdc.gov/vaccines/parents/why-vaccinate/vaccine-decision.htmlGoogle Scholar
Chandler, J. J., & Paolacci, G. (2017). Lie for a dime: When most prescreening responses are honest but most study participants are impostors. Social Psychological and Personality Science, 8(5), 500–508.CrossRefGoogle Scholar
Chen, X., Bennett, P. N., Collins-Thompson, K., & Horvitz, E. (2013, February). Pairwise ranking aggregation in a crowdsourced setting. In Proceedings of the Sixth ACM International Conference on Web Search and Data Mining (pp. 193–202). Computing Machinery.CrossRefGoogle Scholar
Chen, Y., YeckehZaare, I., & Zhang, A. F. (2018). Real or bogus: Predicting susceptibility to phishing with economic experiments. PLoS ONE 13(6): e0198213.Google ScholarPubMed
Cheng, J., Bernstein, M., Danescu-Niculescu-Mizil, C., & Leskovec, J. (2017, February). Anyone can become a troll: Causes of trolling behavior in online discussions. In Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (pp. 1217–1230). Computing Machinery.CrossRefGoogle Scholar
Chesney, T., & Penny, K. (2013). The impact of repeated lying on survey results. SAGE Open, 3(1), 1–9.CrossRefGoogle Scholar
Chou, W. Y. S., Oh, A., & Klein, W. M. (2018). Addressing health-related misinformation on social media. JAMA, 320(23), 2417–2418.CrossRefGoogle ScholarPubMed
Christy, S. M., Gwede, C. K., Sutton, S. K., Chavarria, E., Davis, S. N., Abdulla, R., … & Meade, C. D. (2017). Health literacy among medically underserved: The role of demographic factors, social influence, and religious beliefs. Journal of Health Communication, 22(11), 923–931.CrossRefGoogle ScholarPubMed
Chuck, E. (2018, October). Science says fluoride in water is good for kids. So why are these towns banning it? NBC News. Retrieved from www.nbcnews.com/news/us-news/science-says-fluoride-water-good-kids-so-why-are-these-n920851Google Scholar
Clifford, S., & Jerit, J. (2016). Cheating on political knowledge questions in online surveys: An assessment of the problem and solutions. Public Opinion Quarterly, 80(4), 858–887.CrossRefGoogle Scholar
Cole, S. (2020, March). People are looping videos to fake paying attention in Zoom meetings. Vice. Retrieved from www.vice.com/en_us/article/7kzq5x/looping-videos-to-fake-paying-attention-in-zoom-meetingsGoogle Scholar
Conroy, N. K., Rubin, V. L., & Chen, Y. (2015). Automatic deception detection: Methods for finding fake news. Proceedings of the Association for Information Science and Technology, 52(1), 1–4.CrossRefGoogle Scholar
Cor, M. K., & Sood, G. (2016). Guessing and forgetting: A latent class model for measuring learning. Political Analysis, 24, 226–242.Google Scholar
Cornwell, B., & Lundgren, D. C. (2001). Love on the Internet: Involvement and misrepresentation in romantic relationships in cyberspace vs. realspace. Computers in Human Behavior, 17(2), 197–211.CrossRefGoogle Scholar
Couch, D., & Liamputtong, P. (2007). Online dating and mating: Perceptions of risk and health among online users. Health, Risk & Society, 9(3), 275–294.CrossRefGoogle Scholar
Couch, D., & Liamputtong, P. (2008). Online dating and mating: The use of the internet to meet sexual partners. Qualitative Health Research, 18(2), 268–279.CrossRefGoogle ScholarPubMed
Couch, D., Liamputtong, P., & Pitts, M. (2012). What are the real and perceived risks and dangers of online dating? Perspectives from online daters: Health risks in the media. Health, Risk & Society, 14(7–8), 697–714.CrossRefGoogle Scholar
Crown, D. F., & Spiller, M. S. (1998). Learning from the literature on collegiate cheating: A review of empirical research. Journal of Business Ethics, 17(6), 683–700.Google Scholar
Cumming, D. J., Hornuf, L., Karami, M., & Schweizer, D. (2016). Disentangling crowdfunding from fraudfunding. In Max Planck Institute for Innovation & Competition Research Paper (pp. 1–81). Max Planck Institute.Google Scholar
Curtis, S. R., Rajivan, P., Jones, D. N., & Gonzalez, C. (2018). Phishing attempts among the dark triad: Patterns of attack and vulnerability. Computers in Human Behavior, 87, 174–182.CrossRefGoogle Scholar
Datta, S. S., O’Connor, P. M., Jankovic, D., Muscat, M., Mamou, M. C. B., Singh, S., … & Butler, R. (2018). Progress and challenges in measles and rubella elimination in the WHO European Region. Vaccine, 36(36), 5408–5415.CrossRefGoogle ScholarPubMed
Demestichas, K., Remoundou, K., & Adamopoulou, E. (2020). Food for thought: Fighting fake news and online disinformation. IT Professional, 22(2), 28–34.CrossRefGoogle Scholar
DePaulo, B. M., Kashy, D. A., Kirkendol, S. E., Wyer, M. M., & Epstein, J. A. (1996). Lying in everyday life. Journal of Personality and Social Psychology, 70(5), 979–995.CrossRefGoogle ScholarPubMed
Depaulo, B. M., Malone, B. E., Lindsay, J. J., Muhlenbruck, L., Charlton, K., & Cooper, H. (2003). Cues to deception. Psychological Bulletin, 129(1), 74–118.CrossRefGoogle ScholarPubMed
Difallah, D. E., Demartini, G., & Cudré-Mauroux, P. (2012, April). Mechanical cheat: Spamming schemes and adversarial techniques on crowdsourcing platforms. In CrowdSearch (pp. 26–30). CEUR-WS.Google Scholar
Dingler, T., & Niforatos, E. (2020). Technology-augmented perception and cognition. Human–Computer Interaction Series. Springer International Publishing.Google Scholar
Diviani, N., van den Putte, B., Giani, S., & van Weert, J. C. (2015). Low health literacy and evaluation of online health information: A systematic review of the literature. Journal of Medical Internet Research, 17(5), e112.CrossRefGoogle ScholarPubMed
Donath, J. (1998). Identity and deception in the virtual community. In Smith, M. A. & Kollock, P. (Eds.), Communities in cyberspace (pp. 29–56). Routledge.Google Scholar
Donath, J., & Boyd, D. (2004). Public displays of connection. BT Technology Journal, 22(4), 71–82.CrossRefGoogle Scholar
Drouin, M., Miller, D., Wehle, S. M. J., & Hernandez, E. (2016). Why do people lie online? “Because everyone lies on the internet.” Computers in Human Behavior, 64, 134–142.CrossRefGoogle Scholar
Eickhoff, C., & de Vries, A. P. (2013). Increasing cheat robustness of crowdsourcing tasks. Information Retrieval, 16(2), 121–137.CrossRefGoogle Scholar
Ekman, P. (1997). Deception, lying and demeanour. In Halpen, D. F. & Voiskounsky, A. E. (Eds.), States of mind: American and post-Soviet perspective on contemporary issues in psychology (pp. 92–105). Oxford University Press.Google Scholar
Ellison, N. B., Hancock, J. T., & Toma, C. L. (2012). Profile as promise: A framework for conceptualizing veracity in online dating self-presentations. New Media & Society, 14(1), 45–62.CrossRefGoogle Scholar
Ellison, N., Heino, R., & Gibbs, J. (2006). Managing impressions online: Self-presentation processes in the online dating environment. Journal of Computer-Mediated Communication, 11(2), 415–441.CrossRefGoogle Scholar
Facebook. (n.d.). Fact-checking on Facebook. Facebook. Retrieved from www.facebook.com/business/help/2593586717571940?id=673052479947730Google Scholar
FBI. (2019). 2019 Internet Crime Report. Federal Bureau of Investigation. Retrieved from https://pdf.ic3.gov/2019_IC3Report.pdfGoogle Scholar
FDA. (2019a). Tainted weight loss products. U.S. Food and Drug Administration. Retrieved from www.fda.gov/drugs/medication-health-fraud/tainted-weight-loss-productsGoogle Scholar
FDA. (2020b, April). Beware of fraudulent coronavirus tests, vaccines, and treatments. U.S. Food and Drug Administration. Retrieved from www.fda.gov/consumers/consumer-updates/beware-fraudulent-coronavirus-tests-vaccines-and-treatmentsGoogle Scholar
FDA. (2020c, July). The Bad Ad program. U.S. Food and Drug Administration. Retrieved from www.fda.gov/drugs/office-prescription-drug-promotion/bad-ad-programGoogle Scholar
Feldman, M. D. (2000). Munchausen by Internet: Detecting factitious illness and crisis on the Internet. Southern Medical Journal, 93(7), 669–672.CrossRefGoogle ScholarPubMed
Ferreira, A., & Teles, S. (2019). Persuasion: How phishing emails can influence users and bypass security measures. International Journal of Human-Computer Studies, 125, 19–31.CrossRefGoogle Scholar
FluorideAlert. (n.d.) Fluoride Action Network. Retrieved from https://fluoridealert.orgGoogle Scholar
Fredman, C. (2015, October). Fund me or fraud me? Crowdfunding scams are on the rise. Consumer Reports. Retrieved from www.consumerreports.org/cro/money/crowdfunding-scamGoogle Scholar
Ford, M. (2017, January). The “far right” in America: A brief taxonomy. The Atlantic. Retrieved from www.theatlantic.com/politics/archive/2017/01/far-right-taxonomy/509282/Google Scholar
Foster, D. (2009). Secure, online, high-stakes testing: Science fiction or business reality? Industrial and Organizational Psychology, 2(1), 31–34.CrossRefGoogle Scholar
Fox, S., & Duggan, M. (2013). Health online 2013. Pew Research Center. Retrieved from www.pewresearch.org/internet/2013/01/15/health-online-2013/Google Scholar
Frenkel, S., Decker, B., & Alba, D. (2020). How the “Plandemic” movie and its falsehoods spread widely online. New York Times. Retrieved from www.nytimes.com/2020/05/20/technology/plandemic-movie-youtube-facebook-coronavirus.htmlGoogle Scholar
Frith, U. (2020). Fast lane to slow science. Trends in Cognitive Sciences, 24(1), 1–2.CrossRefGoogle ScholarPubMed
FTC. (February, 2019). FTC brings first case challenging fake paid reviews on an independent retail website. Federal Trade Commission. www.ftc.gov/news-events/press-releases/2019/02/ftc-brings-first-case-challenging-fake-paid-reviews-independentGoogle Scholar
Fulmer, I. S., Barry, B., & Long, D. A. (2009). Lying and smiling: Informational and emotional deception in negotiation. Journal of Business Ethics, 88(4), 691–709.CrossRefGoogle Scholar
Funk, C., & Kennedy, B. (2020, August). Public confidence in scientists has remained stable for decades. Pew Research Center. Retrieved from www.pewresearch.org/fact-tank/2020/08/27/public-confidence-in-scientists-has-remained-stable-for-decades/Google Scholar
Gangavarapu, T., Jaidhar, C. D., & Chanduka, B. (2020). Applicability of machine learning in spam and phishing email filtering: Review and approaches. Artificial Intelligence Review, 53, 1–63.CrossRefGoogle Scholar
George, J. F., Marett, K., & Tilley, P. (2004, January). Deception detection under varying electronic media and warning conditions. In 37th Annual Hawaii International Conference on System Sciences, 2004. Proceedings of the 37th Hawaii International Conference on System Sciences (pp. 1–9). IEEE.Google Scholar
Gershen-Siegel, J. (2019). Perpetrators of crowdfunding fraud can’t hide from the law forever. Entrepreneur. Retrieved from www.entrepreneur.com/article/329995Google Scholar
Ghanem, B., Rosso, P., & Rangel, F. (2018). An emotional analysis of false information in social media and news articles. ACM Transactions on Internet Technology, 20(2), 1–18.CrossRefGoogle Scholar
Gilbert, B. (2019). The 10 most-viewed fake-news stories on Facebook in 2019 were just revealed in a new report. Business Insider. Retrieved from www.businessinsider.com/most-viewed-fake-news-stories-shared-on-facebook-2019–2019–11Google Scholar
Giordano, G., & George, J. (2009). Deception detection, task complexity, and group member experience in computer-mediated group settings. In SIGHCI 2009 Proceedings, 3 (pp. 1–5).Google Scholar
Gonzales, A. L., Kwon, E. Y., Lynch, T., & Fritz, N. (2018). “Better everyone should know our business than we lose our house”: Costs and benefits of medical crowdfunding for support, privacy, and identity. New Media & Society, 20(2), 641–658.CrossRefGoogle Scholar
Grady, D. (1998). Faking pain and suffering in Internet. The New York Times. Retrieved from www.nytimes.com/1998/04/23/technology/faking-pain-and-suffering-in-internet-support-groups.htmlGoogle Scholar
Grandey, A. A. (2003). When “the show must go on”: Surface acting and deep acting as determinants of emotional exhaustion and peer-rated service delivery. Academy of Management Journal, 46(1), 86–96.CrossRefGoogle Scholar
Grazioli, S., & Jarvenpaa, S. L. (2003). Consumer and business deception on the Internet: Content analysis of documentary evidence. International Journal of Electronic Commerce, 7(4), 93–118.Google Scholar
Grebe, E., & Nattrass, N. (2012). AIDS conspiracy beliefs and unsafe sex in Cape Town. AIDS and Behavior, 16(3), 761–773.CrossRefGoogle ScholarPubMed
Greenwald, A. G., & Breckler, S. J. (1985). To whom is the self presented? In Schlenker, B. R. (Ed.), The self and social life (pp. 126–145). McGraw-Hill.Google Scholar
Grijalva, T. C., Nowell, C., & Kerkvliet, J. (2006). Academic honesty and online courses. College Student Journal, 40, 180–185.Google Scholar
Guess, A., Nagler, J., & Tucker, J. (2019). Less than you think: Prevalence and predictors of fake news dissemination on Facebook. Science Advances, 5(1), eaau4586.CrossRefGoogle ScholarPubMed
Guess, A., Nyhan, B., & Reifler, J. (2018). Selective exposure to misinformation: Evidence from the consumption of fake news during the 2016 US presidential campaign. European Research Council, 9(3), 4.Google Scholar
Guillory, J., & Hancock, J. T. (2012). The effect of LinkedIn on deception in resumes. Cyberpsychology, Behavior, and Social Networking, 15(3), 135–140.CrossRefGoogle ScholarPubMed
Guo, J., & Drasgow, F. (2010). Identifying cheating on unproctored internet tests: The Z‐test and the likelihood ratio test. International Journal of Selection and Assessment, 18(4), 351–364.CrossRefGoogle Scholar
Hall, J. A., Park, N., Song, H., & Cody, M. J. (2010). Strategic misrepresentation in online dating: The effects of gender, self-monitoring, and personality traits. Journal of Social and Personal Relationships, 27(1), 117–135.CrossRefGoogle Scholar
Hample, D. (1980). Purposes and effects of lying. Southern Speech Communication Journal, 46(1), 33–47.CrossRefGoogle Scholar
Hancock, J. T. (2007). On lying and being lied to: A Linguistic analysis of deception in computer-mediated communication. Discourse Processes, 1, 12–14.Google Scholar
Hancock, J. T., Birnholtz, J., Bazarova, N., Guillory, J., Perlin, J., & Amos, B. (2009, April). Butler lies: Awareness, deception and design. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 517–526). Computing Machinery.CrossRefGoogle Scholar
Hancock, J. T., Thom-Santelli, J., & Ritchie, T. (2004, April). Deception and design: The impact of communication technology on lying behavior. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 129–134). Computing Machinery.CrossRefGoogle Scholar
Hartwig, M., Granhag, P. A., Strömwall, L. A., & Vrij, A. (2005). Detecting deception via strategic disclosure of evidence. Law and Human Behavior, 29(4), 469–484.CrossRefGoogle ScholarPubMed
Hasher, L., Goldstein, D., & Toppino, T. (1977). Frequency and the conference of referential validity. Journal of Verbal Learning and Verbal Behavior, 16(1), 107–112.CrossRefGoogle Scholar
Hauser, D., Paolacci, G., & Chandler, J. (2019). Common concerns with MTurk as a participant pool: Evidence and solutions. In Kardes, F. R., Herr, P. M., & Schwarz, N. (Eds.), Handbook of research methods in consumer psychology (pp. 319–337). Routledge/Taylor & Francis Group.Google Scholar
Heller, J. (2015). Rumors and realities: Making sense of HIV/AIDS conspiracy narratives and contemporary legends. American Journal of Public Health, 105(1), e43–e50.CrossRefGoogle ScholarPubMed
Hogan, R., Jones, W. H., & Cheek, J. M. (1985). Socioanalytic theory: An alternative to armadillo psychology. In Schlenker, B. R. (Ed.), The self and social life (pp. 175–198). McGraw-Hill.Google Scholar
Hollingshead, A. (2000). Truth and lying in computer-mediated groups. In Neale, M. A., Mannix, E. A., and Griffith, T. (Eds.), Research in managing groups and teams (volume 3: technology and teams) (pp. 157–173). JAI Press.CrossRefGoogle Scholar
Horn, D. B., Karasik, L., & Olsen, J. S. (2002, April). The effects of spatial and temporal video distortion on lie detection performance. In CHI’02 Extended Abstracts on Human Factors in Computing Systems (pp. 1–2). Association for Computing Machinery.Google Scholar
House, D., & Raja, M. K. (2019) Phishing: Message appraisal and the exploration of fear and self-confidence. Behaviour & Information Technology, 11, 1–22.Google Scholar
Howe, J. (2006). The rise of crowdsourcing. Wired. Retrieved from www.wired.com/2006/06/crowds/Google Scholar
Howe, J. (2008). Crowdsourcing: Why the power of the crowd is driving the future of business. Random House.Google Scholar
Human Rights Watch. (May, 2020). Covid-19 fueling anti-Asian racism and xenophobia worldwide. Human Rights Watch. www.hrw.org/news/2020/05/12/covid-19-fueling-anti-asian-racism-and-xenophobia-worldwideGoogle Scholar
Hyman, R. (1989). The psychology of deception. Annual Review of Psychology, 40(1), 133–154.CrossRefGoogle Scholar
Imam, J. (2020, May). Catfishing during coronavirus: How and old Internet scam still tricks people. NBC News. www.nbcnews.com/tech/tech-news/catfishing-during-coronavirus-how-old-internet-scam-still-tricks-people-n1197736Google Scholar
Innes, M., Dobreva, D., & Innes, H. (2019). Disinformation and digital influencing after terrorism: Spoofing, truthing and social proofing. Contemporary Social Science, 2, 1–15.Google Scholar
International Test Commission. (2005, July). ITC guidelines on computer-based and internet-delivered testing. International Journal of Testing, 6(2), 143–171.Google Scholar
Ipeirotis, P. G. (2010). Demographics of Mechanical Turk. Technical report no. CeDER-10–01. New York University. Retrieved from http://hdl.handle.net/2451/29585Google Scholar
Johar, G. V. (1995). Consumer involvement and deception from implied advertising claims. Journal of Marketing Research, 32(3), 267–279.CrossRefGoogle Scholar
Jones, E. E., & Pittman, T. S. (1982). Toward a general theory of strategic self-presentation. In Suls, J. (Ed.), Psychological perspectives on the self (Vol. I, pp. 231–262). Erlbaum.Google Scholar
Jones, E. E., & Wortman, C. (1972). Ingratiation: An attributional approach. General Learning Press.Google Scholar
Jones, E. E., Gergen, K. J., Gumpert, P., & Thibaut, J. W. (1965). Some conditions affecting the use of ingratiation to influence performance evaluation. Journal of Personality and Social Psychology, 1, 613–625.CrossRefGoogle ScholarPubMed
Jones, E. E., Gergen, K. J., & Jones, R. G. (1963). Tactics of ingratiation among leaders and subordinates in a status hierarchy. Psychological Monographs: General and Applied, 77(3), 1.CrossRefGoogle Scholar
Kan, I. P., & Drummey, A. B. (2018). Do imposters threaten data quality? An examination of worker misrepresentation and downstream consequences in Amazon’s Mechanical Turk workforce. Computers in Human Behavior, 83, 243–253.CrossRefGoogle Scholar
Karim, M. N., Kaminsky, S. E., & Behrend, T. S. (2014). Cheating, reactions, and performance in remotely proctored testing: An exploratory experimental study. Journal of Business and Psychology, 29(4), 555–572.CrossRefGoogle Scholar
Katz, E. Blumler, J. G., & Gurevitch, M. (1974). Uses and gratifications research. Public Opinion Quarterly, 37, 509–523.CrossRefGoogle Scholar
Kaufmann, N., Schulze, T., & Veit, D. (2011, August). More than fun and money. Worker Motivation in Crowdsourcing – A Study on Mechanical Turk. In Amcis (pp. 1–11). Association for Information Systems (AIS).Google Scholar
Kay, A. C., Gaucher, D., Napier, J. L., Callan, M. J., & Laurin, K. (2008). God and the government: Testing a compensatory control mechanism for the support of external systems. Journal of Personality and Social Psychology, 95(1), 18–35.CrossRefGoogle ScholarPubMed
Kempe, D., Kleinberg, J., & Tardos, É. (2003, August). Maximizing the spread of influence through a social network. In Proceedings of the ninth ACM SIGKDD international conference on knowledge discovery and data mining (pp. 137–146). Association for Computing Machinery.CrossRefGoogle Scholar
Kim, B., Lee, D. Y., & Kim, B. (2019): Deterrent effects of punishment and training on insider security threats: A field experiment on phishing attacks. Behaviour & Information Technology, 11, 1–20.Google Scholar
King, C. G., Guyette, R. W. Jr, & Piotrowski, C. (2009). Online exams and cheating: An empirical analysis of business students’ views. Journal of Educators Online, 6(1), 1–11.CrossRefGoogle Scholar
Kittur, A., Chi, E. H., & Suh, B. (2008, April). Crowdsourcing user studies with Mechanical Turk. In Proceedings of the SIGCHI conference on human factors in computing systems (pp. 453–456). Association for Computing Machinery.CrossRefGoogle Scholar
Kowalski, R. M., Giumetti, G. W., Schroeder, A. N., & Lattanner, M. R. (2014). Bullying in the digital age: A critical review and meta-analysis of cyberbullying research among youth. Psychological Bulletin, 140(4), 1073–1137.CrossRefGoogle Scholar
Krämer, N. C., & Winter, S. (2008). Impression management 2.0: The relationship of self-esteem, extraversion, self-efficacy, and self-presentation within social networking sites. Journal of Media Psychology, 20(3), 106–116.CrossRefGoogle Scholar
Kumar, S., & Shah, N. (2018). False information on web and social media: A survey. https://arxiv.org/abs/1804.08559.Google Scholar
Kumar, S., West, R., & Leskovec, J. (2016, April). Disinformation on the web: Impact, characteristics, and detection of Wikipedia hoaxes. In Proceedings of the 25th international conference on World Wide Web (pp. 1–12). International World Wide Web Conferences Steering Committee.Google Scholar
Kunda, Z. (1990). The case for motivated reasoning. Psychological Bulletin, 108(3), 480–498.CrossRefGoogle ScholarPubMed
Kwang, T., & Swann, W. B. (2010). Do people embrace praise even when they feel unworthy? A review of critical tests of self-enhancement versus self-verification. Personality and Social Psychology Review, 14 (3), 263–280.CrossRefGoogle ScholarPubMed
Kylstra, C. (2019, August). Who cares what celebrities think about vaccines? The New York Times. Retrieved from www.nytimes.com/2019/08/23/opinion/anti-vaccine.htmlGoogle Scholar
Lampe, C. A., Ellison, N., & Steinfield, C. (2007, April). A familiar face (book) profile elements as signals in an online social network. In Proceedings of the SIGCHI conference on Human factors in computing systems (pp. 435–444). Association for Computing Machinery.CrossRefGoogle Scholar
Landers, R. N., & Sackett, P. R. (2012). Offsetting performance losses due to cheating in unproctored internet‐based testing by increasing the applicant pool. International Journal of Selection and Assessment, 20(2), 220–228.CrossRefGoogle Scholar
Larson, H. J., Cooper, L. Z., Eskola, J., Katz, S. L., & Ratzan, S. (2011). Addressing the vaccine confidence gap. The Lancet, 378, 526–535.CrossRefGoogle ScholarPubMed
LaTour, K. A., & LaTour, M. S. (2009). Positive mood and susceptibility to false advertising. Journal of Advertising, 38(3), 127–142.CrossRefGoogle Scholar
Lauckner, C., Truszczynski, N., Lambert, D., Kottamasu, V., Meherally, S., Schipani-McLaughlin, A. M., … & Hansen, N. (2019). “Catfishing,” cyberbullying, and coercion: An exploration of the risks associated with dating app use among rural sexual minority males. Journal of Gay & Lesbian Mental Health, 23(3), 289–306.CrossRefGoogle Scholar
Lazer, D., Baum, M., Grinberg, N., Friedlan, L., Joseph, K., Hobbs, W. & Mattsson, C. (2017, May). Combating fake news: An agenda for research and action. Retrieved from www.sipotra.it/old/wp-content/uploads/2017/06/Combating-Fake-News.pdfGoogle Scholar
Leary, M. R., & Kowalski, R. M. (1990). Impression management: A literature review and two-component model. Psychological Bulletin, 107(1), 34–47.CrossRefGoogle Scholar
Lee, C. S., & Ma, L. (2012). News sharing in social media: The effect of gratifications and prior experience. Computers in Human Behavior, 28(2), 331–339.CrossRefGoogle Scholar
Lehtonen, J. (1988). The information society and the new competence. The American Behavioral Scientist, 32, 104–112.CrossRefGoogle Scholar
Levashina, J., & Campion, M. A. (2007). Measuring faking in the employment interview: Development and validation of an interview faking behavior scale. Journal of Applied Psychology, 92(6), 1638.CrossRefGoogle ScholarPubMed
Lewandowsky, Kecker, & Cook, . (2017). Beyond misinformation: Understanding and coping with the “Post Truth” era. Journal of Applied Research in Memory and Cognition, 6, 353–369.CrossRefGoogle Scholar
Lewandowsky, S., Ecker, U. K., Seifert, C. M., Schwarz, N., & Cook, J. (2012). Misinformation and its correction: Continued influence and successful debiasing. Psychological Science in the Public Interest, 13(3), 106–131.CrossRefGoogle ScholarPubMed
Litman, L., Robinson, J., & Rosenzweig, C. (2015). The relationship between motivation, monetary compensation, and data quality among US-and India-based workers on Mechanical Turk. Behavior Research Methods, 47(2), 519–528.CrossRefGoogle ScholarPubMed
Liu, Z., Liu, L., & Li, H. (2012). Determinants of information retweeting in microblogging. Internet Research, 22(4), 443–466.CrossRefGoogle Scholar
Lopez, J., & Hillygus, D. S. (2018, March). Why so serious? Survey trolls and misinformation. SSRN. https://ssrn.com/abstract=3131087 or http://dx.doi.org/10.2139/ssrn.3131087CrossRefGoogle Scholar
Lowry, P. B., D’Arcy, J., Hammer, B., & Moody, G. D. (2016). “Cargo Cult” science in traditional organization and information systems survey research: A case for using nontraditional methods of data collection, including Mechanical Turk and online panels. The Journal of Strategic Information Systems, 25(3), 232–240.CrossRefGoogle Scholar
Lowry, P. B., Zhang, J., Wang, C., & Siponen, M. (2016). Why do adults engage in cyberbullying on social media? An integration of online disinhibition and deindividuation effects with the social structure and social learning model. Information Systems Research, 27(4), 962–986.CrossRefGoogle Scholar
Lyons, T. (2018, June 14). Hard questions: How Is Facebook’s fact-checking program working? Facebook. Retrieved from https://about.fb.com/news/2018/06/hard-questions-fact-checking/Google Scholar
Ma, M., & Agarwal, R. (2007). Through a glass darkly: Information technology design, identity verification, and knowledge contribution in online communities. Information Systems Research, 18(1), 42–67.CrossRefGoogle Scholar
Macht, S. A., & Weatherston, J. (2014). The benefits of online crowdfunding for fund‐seeking business ventures. Strategic Change, 23(1‐2), 1–14.CrossRefGoogle Scholar
Makkai, T., & Braithwaite, J. (1994). Reintegrative shaming and compliance with regulatory standards. Criminology, 32(3), 361–385.CrossRefGoogle Scholar
Makransky, G., & Glas, C. A. (2011). Unproctored internet test verification: Using adaptive confirmation testing. Organizational Research Methods, 14(4), 608–630.CrossRefGoogle Scholar
Malbon, J. (2013). Taking fake online consumer reviews seriously. Journal of Consumer Policy, 36(2), 139–157.CrossRefGoogle Scholar
Markowitz, D. M., & Hancock, J. T. (2018). Deception in mobile dating conversations. Journal of Communication, 68(3), 547–569.CrossRefGoogle Scholar
Marwick, A., & Boyd, D. (2011). To see and be seen: Celebrity practice on Twitter. Convergence, 17(2), 139–158.CrossRefGoogle Scholar
Mason, W., & Suri, S. (2012). Conducting behavioral research on Amazon’s Mechanical Turk. Behavior Research Methods, 44(1), 1–23.CrossRefGoogle ScholarPubMed
Mavlanova, T., & Benbunan-Fich, R. (2010). Counterfeit products on the Internet: The role of seller-level and product-level information. International Journal of Electronic Commerce, 15(2), 79–104.CrossRefGoogle Scholar
McAlvanah, P., Anderson, K., Letzler, R., & Mountjoy, J. (2015, April). Fraudulent advertising susceptibility: An experimental approach. Federal Trade Commission Bureau of Economics, 325, 1–106.Google Scholar
McCarthy, T. (2018, October). Celebrity death hoaxes: 6 starts who had to tell the world they’re still alive. Fox News. Retrieved from www.foxnews.com/entertainment/celebrity-death-hoaxes-6-stars-who-have-had-to-tell-fans-theyre-not-deadGoogle Scholar
Metz, R. & O’Sullivan, D. (2019). A deepfake video of Mark Zuckerberg presents a new challenge for Facebook. CNN. Retrieved from www.cnn.com/2019/06/11/tech/zuckerberg-deepfake/index.htmlGoogle Scholar
Milman, O. (2020, February). Revealed: Quarter of all tweets about climate crisis produced by bots. The Guardian. Retrieved from www.theguardian.com/technology/2020/feb/21/climate-tweets-twitter-bots-analysisGoogle Scholar
Misra, J. (2019, April). Voter turnout raters among all voting age and major racial and ethical groups were higher than in 2014. U.S. Census Bureau. Retrieved from www.census.gov/library/stories/2019/04/behind-2018-united-states-midterm-election-turnout.htmlGoogle Scholar
Mitchell, A., Jurkowitz, M., Oliphant, J., & Shearer, E. (2020, June). Three months in, many Americans see exaggeration, conspiracy theories, and partisanship in COVID-19 news. Pew Research Center. Retrieved from www.journalism.org/2020/06/29/three-months-in-many-americans-see-exaggeration-conspiracy-theories-and-partisanship-in-covid-19-news/Google Scholar
Mitra, A., Raymond, M. A., & Hopkins, C. D. (2008). Can consumers recognize misleading advertising content in a media rich online environment? Psychology & Marketing, 25(7), 655–674.CrossRefGoogle Scholar
Morgan, J. (2017, October). Facebook and Google need to own their role in spreading misinformation – and fix it. CNN. Retrieved from www.cnn.com/2017/10/09/opinions/social-media-platforms-spreading-disinformation-opinion-morgan/index.htmlGoogle Scholar
Mosseri, A. (2017). Working to stop misinformation and false news. Facebook Newsroom. Retrieved from https://about.fb.com/news/2017/04/working-to-stop-misinformation-and-false-newsGoogle Scholar
Mueller-Hanson, R. A., Heggestad, E. D., & Thornton, G. C. (2006). Individual differences in impression management: An exploration of the psychological processes underlying faking. Psychology Science, 48(3), 288–312.Google Scholar
Murphy, H. (2019, October 14). ABC apologizes for showing video from U.S. gun range in report on Syria. The New York Times. Retrieved from www.nytimes.com/2019/10/14/business/media/turkey-syria-kentucky-gun-range.htmlGoogle Scholar
Murphy, K., & Harris, N. (2007). Shaming, shame and recidivism: A test of reintegrative shaming theory in the white-collar crime context. The British Journal of Criminology, 47(6), 900–917.CrossRefGoogle Scholar
Muse, K., McManus, F., Leung, C., Meghreblian, B., & Williams, J. M. G. (2012). Cyberchondriasis: Fact or fiction? A preliminary examination of the relationship between health anxiety and searching for health information on the Internet. Journal of Anxiety Disorders, 26(1), 189–196.CrossRefGoogle ScholarPubMed
Mustafaraj, E., & Metaxas, P. T. (2017, June). The fake news spreading plague: Was it preventable? In Proceedings of the 2017 ACM on Web Science Conference (pp. 235–239). Association for Computing Machinery.CrossRefGoogle Scholar
Naglieri, J. A., Drasgow, F., Schmit, M., Handler, L., Prifitera, A., Margolis, A., & Velasquez, R. (2004). Psychological testing on the Internet: New problems, old issues. American Psychologist, 59(3), 150–162.CrossRefGoogle ScholarPubMed
Nickerson, R. S. (1998). Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology, 2(2), 175–220.CrossRefGoogle Scholar
Nonis, S. A., & Swift, C. O. (1998). Deterring cheating behavior in the marketing classroom: An analysis of the effects of demographics, attitudes, and in-class deterrent strategies. Journal of Marketing Education, 20(3), 188–199.CrossRefGoogle Scholar
O’Donoghue, A. C., Boudewyns, V., Aikin, K. J., Geisen, E., Betts, K. R. & Southwell, B. G. (2015). Awareness of the Food and Drug Administration’s Bad Ad program and education regarding pharmaceutical advertising: A national survey of prescribers in ambulatory care settings. Journal of Health Communication, 20(11), 1330–1336.CrossRefGoogle ScholarPubMed
Oh, H. J., & Lee, H. (2019). When do people verify and share health rumors on social media? The effects of message importance, health anxiety, and health literacy. Journal of Health Communication, 24(11), 837–847.CrossRefGoogle ScholarPubMed
Oliver, J. E., & Wood, T. (2014). Medical conspiracy theories and health behaviors in the United States. JAMA Internal Medicine, 174(5), 817–818.CrossRefGoogle ScholarPubMed
Osmundsen, M., Bor, A., Vahlstrup, P. B., Bechmann, A., & Petersen, M. B. (2020). Partisan polarization is the primary psychological motivation behind “fake news” sharing on Twitter. American Political Science Review, 115(3), 999–1015.CrossRefGoogle Scholar
Ott, M., Cardie, C., & Hancock, J. (2012, April). Estimating the prevalence of deception in online review communities. In Proceedings of the 21st international conference on World Wide Web (pp. 201–210). Association for Computing Machinery.CrossRefGoogle Scholar
Ott, M., Choi, Y., Cardie, C., & Hancock, J. T. (2011). Finding deceptive opinion spam by any stretch of the imagination. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics (pp. 309–319). Association for Computational Linguistics.Google Scholar
Page, D. (2019, July). Kittenfishing: The common dating trend you’re probably (slightly) guilty of. NBC News. www.nbcnews.com/better/lifestyle/kittenfishing-common-dating-trend-you-re-likely-guilty-ncna1030121Google Scholar
Parkinson, H. J. (2016). Click and elect: How fake news helped Donald Trump win a real election. The Guardian. Retrieved from www.theguardian.com/commentisfree/2016/nov/14/fake-news-donald-trump-election-alt-right-social-media-tech-companiesGoogle Scholar
Parsons, K., Butavicius, M., Delfabbro, P., & Lillie, M. (2019). Predicting susceptibility to social influence in phishing emails. International Journal of Human-Computer Studies, 128, 17–26.CrossRefGoogle Scholar
Pauls, C. A., & Crost, N. W. (2004). Effects of faking on self-deception and impression management scales. Personality and Individual Differences, 37, 1137–1151.CrossRefGoogle Scholar
Pearlman, K. (2009). Unproctored Internet testing: Practical, legal, and ethical concerns. Industrial and Organizational Psychology, 2(1), 14–19.CrossRefGoogle Scholar
Pennycook, G., & Rand, G. (2018). Who falls for fake news? The roles of bullshit receptivity, overclaiming, familiarity, and analytic thinking. Journal of Personality, 88, 185–200.CrossRefGoogle Scholar
Pennycook, G., Bear, A., Collins, E. T., & Rand, D. G. (2020). The implied truth effect: Attaching warnings to a subset of fake news headlines increases perceived accuracy of headlines without warnings. Management Science. Articles in Advance, 1–14.CrossRefGoogle Scholar
Pennycook, G., Cannon, T. D., & Rand, D. G. (2018). Prior exposure increases perceived accuracy of fake news. Journal of Experimental Psychology: General, 147(12), 1865–1880.CrossRefGoogle ScholarPubMed
Pérez-Rosas, V., Kleinberg, B., Lefevre, A., & Mihalcea, R. (2017). Automatic detection of fake news. https://arxiv.org/abs/1708.07104.Google Scholar
Petty, R. E., & Cacioppo, J. T. (1986). The elaboration likelihood model of persuasion. In Communication and persuasion (pp. 1–24). Springer, New York.CrossRefGoogle Scholar
Poddar, A., Banerjee, S., & Sridhar, K. (2019). False advertising or slander? Using location based tweets to assess online rating-reliability. Journal of Business Research, 99, 390–397.CrossRefGoogle Scholar
Polage, D. C. (2012). Making up history: False memories of fake news stories. Europe’s Journal of Psychology, 8(2), 245–250.CrossRefGoogle Scholar
Pulman, A., & Taylor, J. (2012). Munchausen by Internet: Current research and future directions. Journal of Medical Internet Research, 14(4), e115.CrossRefGoogle ScholarPubMed
Quora. (2018, September). Some think big pharma is suppressing a cure for cancer. Here’s why that could never happen. Forbes. Retrieved from www.forbes.com/sites/quora/2018/09/10/some-think-big-pharma-is-suppressing-a-cure-for-cancer-heres-why-that-could-never-happen/#6170e31c419cGoogle Scholar
RAND. (2019, December). Tools that fight disinformation online. RAND Corporation. Retrieved from www.rand.org/research/projects/truth-decay/fighting-disinformation/search.htmlGoogle Scholar
Read, M. (2016, November). Donald Trump won because of Facebook. Intelligencer. Retrieved from https://nymag.com/intelligencer/2016/11/donald-trump-won-because-of-facebook.htmlGoogle Scholar
Renwick, M. J., & Mossialos, E. (2017). Crowdfunding our health: Economic risks and benefits. Social Science & Medicine, 191, 48–56.CrossRefGoogle ScholarPubMed
Robock, Z. (2014). The risk of money laundering through crowdfunding: A funding portal’s guide to compliance and crime fighting. Michigan Business & Entrepreneurial Law Review, 4, 113.CrossRefGoogle Scholar
Román, S. (2010). Relational consequences of perceived deception in online shopping: The moderating roles of type of product, consumer’s attitude toward the Internet and consumer’s demographics. Journal of Business Ethics, 95(3), 373–391.CrossRefGoogle Scholar
Roozenbeek, J., & Van Der Linden, S. (2018). The fake news game: Actively inoculating against the risk of misinformation. Journal of Risk Research, 22(5), 570–580.CrossRefGoogle Scholar
Rowatt, W. C., Cunninghan, M. R., & Druen, P. B. (1998). Deception to get a date. Personality and Social Psychology Bulletin, 24(11), 1228–1242.CrossRefGoogle Scholar
Rubin, V. L., Conroy, N., Chen, Y., & Cornwell, S. (2016, June). Fake news or truth? using satirical cues to detect potentially misleading news. In Proceedings of the second workshop on computational approaches to deception detection (pp. 7–17). Association for Computational Linguistics.CrossRefGoogle Scholar
Sagarin, B. J., Cialdini, R. B., Rice, W. E., & Serna, S. B. (2002). Dispelling the illusion of invulnerability: The motivations and mechanisms of resistance to persuasion. Journal of Personality and Social Psychology, 83(3), 526–541.CrossRefGoogle ScholarPubMed
Sanfilippo, M., Yang, S., & Fichman, P. (2017). Managing online trolling: From deviant to social and political trolls. In Proceedings of the 50th Hawaii International Conference on Systems Sciences (pp. 1802–1811).CrossRefGoogle Scholar
Schlenker, B. R. (1980). Impression management: The self-concept. Social Identity, and Interpersonal Relations. Brooks/Cole.Google Scholar
Schlenker, B. R. (1985). Identity and self-identification. In Schlenker, B. R. (Ed.), The self and social life (pp. 65–99). McGraw-Hill.Google Scholar
Schneider, D. J. (1981). Tactical self-presentations: Toward a broader conception. In Tedeschi, J. T. (Ed.), Impression management theory and social psychological research (pp. 23–40). Academic Press.CrossRefGoogle Scholar
Schneiderman, A. G. (2013, September). A. G. Schneiderman announces agreement with 19 companies to stop writing fake online reviews and pay more than $350,000 in fines. New York State Attorney. Retrieved from https://ag.ny.gov/press-release/2013/ag-schneiderman-announces-agreement-19-companies-stop-writing-fake-online-reviewsGoogle Scholar
Schroeder, A. N., & Cavanaugh, J. M. (2018). Fake it’til you make it: Examining faking ability on social media pages. Computers in Human Behavior, 84, 29–35.CrossRefGoogle Scholar
Schroeder, A.N., Bricka, T. M., & Whitaker, J. H. (2019). Work design in a digitized gig economy. Human Resource Management Review. Advance online publication.Google Scholar
Shachaf, P., & Hara, N. (2010). Beyond vandalism: Wikipedia trolls. Journal of Information Science, 36(3), 357.370.CrossRefGoogle Scholar
Shafqat, W., Lee, S., Malik, S., & Kim, H. C. (2016, April). The language of deceivers: Linguistic features of crowdfunding scams. In Proceedings of the 25th International Conference Companion on World Wide Web (pp. 99–100). World Wide Web Conferences Steering Committee.Google Scholar
Sharabi, L. L., & Caughlin, J. P. (2019). Deception in online dating: Significance and implications for the first offline date. New Media & Society, 21(1), 229–247.CrossRefGoogle Scholar
Sharma, K., Qian, F., Jiang, H., Ruchansky, N., Zhang, M., & Liu, Y. (2018). Combating fake news: A survey on identification and mitigation techniques. ACM Transactions on Intelligent Systems and Technology, 10(3), 1–42.CrossRefGoogle Scholar
Shi, J., Hu, P., Lai, K. K., & Chen, G. (2018). Determinants of users’ information dissemination behavior on social networking sites. Internet Research, 28(2), 393–418.CrossRefGoogle Scholar
Shi, S., Brant, A. R., Sabolch, A., & Pollom, E. (2019). False news of a cannabis cancer cure. Cureus, 11(1), 1–11.Google ScholarPubMed
Silverman, C., Feder, J. L., Cvetkovska, S., & Belford, A. (2018, July). Macedonia’s pro-Trump fake news industry had American links, and is under investigation for possible Russia ties. Buzzfeed News. Retrieved from www.buzzfeednews.com/article/craigsilverman/american-conservatives-fake-news-macedonia-paris-wade-libertGoogle Scholar
Simons, J. J., Phillips, N. J., Chopra, R., Slaughter, R. K., & Wilson, C. S. (2018, October). Protecting Older Consumers. A report of the Federal Trade Commission to Congress. Federal Trade Commission. https://www.ftc.gov/system/files/documents/reports/protecting-older-consumers-2017-2018-report-congress-federal-trade-commission/protecting_older_consumers_-_ftc_report_10-18-18.pdf.Google Scholar
Slavick, S. J. (2019, April). Online false advertising. American Bar Association. Retrieved from www.americanbar.org/groups/gpsolo/publications/gp_solo/2011/march/online_false_advertising_risks/Google Scholar
Smith, M. E., Hancock, J. T., Reynolds, L., & Birnholtz, J. (2014). Everyday deception or a few prolific liars? The prevalence of lies in text messaging. Computers in Human Behavior, 41, 220–227.CrossRefGoogle Scholar
Snell, A. F., Sydell, E. J., & Lueke, S. B. (1999). Towards a theory of applicant faking: Integrating studies of deception. Human Resource Management Review, 9(2), 219–242.CrossRefGoogle Scholar
Society for Human Resource Management. (2016, January). SHRM survey findings: Using social media for talent acquisition – recruitment and screening. Society for Human Resource Management. Retrieved from www.shrm.org/research/surveyfindings/pages/social-media-recruiting-screening-2015.aspxGoogle Scholar
Soleymani, M., & Larson, M. (2010). Crowdsourcing for affective annotation of video: Development of a viewer-reported Boredom Corpus. In Workshop on Crowdsourcing for Search Evaluation, SIGIR 2010.Google Scholar
Stengers, I. (2018). Another science is possible: A manifesto for slow science. Polity Press.Google Scholar
Suler, J. (2004). The online disinhibition effect. Cyberpsychology & Behavior, 7(3), 321–326.CrossRefGoogle ScholarPubMed
Sullivan, D. P. (2016). An integrated approach to preempt cheating on asynchronous, objective, online assessments in graduate business classes. Online Learning, 20(3), 195–209.CrossRefGoogle Scholar
Swann, W. B. (1983). Self-verification: Bringing social reality into harmony with the self. In Suls, J. and Greenwalk, A. G. (Eds.), Psychological Perspectives on the Self, 2. (pp. 33–66). Erlbaum.Google Scholar
Swire-Thompson, B., & Lazer, D. (2020). Public health and online misinformation: Challenges and recommendations. Annual Review of Public Health, 41, 433–451.CrossRefGoogle ScholarPubMed
Symantec (2018, March). Internet security threat report. Symantec. Retrieved from http://images.mktgassets.symantec.com/Web/Symantec/%7B3a70beb8-c55d-4516–98ed-1d0818a42661%7D_ISTR23_Main-FINAL-APR10.pdf?aid=elq_Google Scholar
Tandoc, E. C. Jr, Lim, Z. W., & Ling, R. (2017). Defining “fake news”: A typology of scholarly definitions. Digital Journalism, 6(2), 137–153.CrossRefGoogle Scholar
Taylor, A. (2015). 7 times the Onion was lost in translation. Washington Post. Retrieved from www.washingtonpost.com/news/worldviews/wp/2015/06/02/7-times-the-onion-was-lost-in-translation/Google Scholar
Tedeschi, J. T. (1986). Private and public experiences and the self. In Public Self and Private Self (pp. 1–20). Springer, New York.Google Scholar
Teoh, D. (2019). The power of social media for HPV vaccination – Not fake news! American Society of Clinical Oncology Educational Book, 39, 75–78.CrossRefGoogle ScholarPubMed
Tetlock, P. E. (1981). Pre- to postelection shifts in presidential phetoic: Impression management or cognitive adjustment? Attitudes and Social Cognition, 41(2), 207–212.Google Scholar
The Economist. (2015, October). Five-star fakes: The evolving fight against sham reviews. The Economist. Retrieved from www.economist.com/business/2015/10/22/five-star-fakesGoogle Scholar
The Economist. (2020, September). Covid-19 has forced a radical shift in working habits. The Economist. Retrieved from www.economist.com/briefing/2020/09/12/covid-19-has-forced-a-radical-shift-in-working-habitsGoogle Scholar
The Ranking Committee. (2020, May). Biden vetting rumors are circulating. Here are the VP finalists we see. The Washington Post. Retrieved from www.washingtonpost.com/opinions/2020/05/22/biden-vetting-rumors-are-circulating-here-are-vp-finalists-we-see/?arc404=trueGoogle Scholar
Thompson, N., Wang, X., & Daya, P. (2019). Determinants of news sharing behavior on social media. Journal of Computer Information Systems, 60(6), 1–9.Google Scholar
Tippins, N. T., Beaty, J., Drasgow, F., Gibson, W. M., Pearlman, K., Segall, D. O., & Shepherd, W. (2006). Unproctored internet testing in employment settings. Personnel Psychology, 59(1), 189–225.CrossRefGoogle Scholar
Toews, R. (2020). Deepfakes are going to wreak havoc on society. We are not prepared. Forbes. Retrieved from www.forbes.com/sites/robtoews/2020/05/25/deepfakes-are-going-to-wreak-havoc-on-society-we-are-not-prepared/#495660357494Google Scholar
Toma, C. L. (2017). Developing online deception literacy while looking for love. Media, Culture & Society, 39(3), 423–428.CrossRefGoogle Scholar
Toma, C. L., & Hancock, J. T. (2010). Looks and lies: The role of physical attractiveness in online dating self-presentation and deception. Communication Research, 37(3), 335–351.CrossRefGoogle Scholar
Toma, C. L., Hancock, J. T., & Ellison, N. B. (2008). Separating fact from fiction: An examination of deceptive self-presentation in online dating profiles. Personality and Social Psychology Bulletin, 34(8), 1023–1036.CrossRefGoogle ScholarPubMed
Tong, C., Gill, H., Li, J., Valenzuela, S., & Rojas, H. (2020). “Fake news is anything they say!” – Conceptualization and weaponization of fake news among the American public. Mass Communication and Society, 23(5), 755–778.CrossRefGoogle Scholar
Tooke, W., & Camire, L. (1991). Patterns of deception in intersexual and intrasexual mating strategies. Ethology and Sociobiology, 12, 345–364.CrossRefGoogle Scholar
Triplett, N. (1900). The psychology of conjuring deceptions. The American Journal of Psychology, 11, 439–510.CrossRefGoogle Scholar
Tsikerdekis, M., & Zeadally, S. (2014). Online deception in social media. Communications of the ACM, 57(9), 72–80.CrossRefGoogle Scholar
Tsikerdekis, M., & Zeadally, S. (2020). Detecting online content deception. IT Professional, 22(2), 35–44.CrossRefGoogle Scholar
Turner, P. (1993). I heard it through the grapevine: Rumor in African American culture. University of California Press.CrossRefGoogle Scholar
Turner, R. E., Edgley, C., & Olmstead, G. (1975). Information control in conversations: Honesty is not always the best policy. Kansas Journal of Sociology, 11(1), 69–89.Google Scholar
United Nations. (May, 2020). COVID-19: UN counters pandemic-related hate and xenophonia. United Nations. Retrieved from www.un.org/en/coronavirus/covid-19-un-counters-pandemic-related-hate-and-xenophobiaGoogle Scholar
Utz, S. (2005). Types of deception and underlying motivation: What people think. Social Science Computer Review, 23(1), 49–56.CrossRefGoogle Scholar
Valkenburg, P. M., Schouten, A. P., & Peter, J. (2005). Adolescents’ identity experiments on the Internet. New Media & Society, 7(3), 383–402.CrossRefGoogle Scholar
van Kessel, P. (2018). Is cybersecurity about more than protection? EY Global Information Security Survey 2018–19. EY. Retrieved from www.phishingbox.com/assets/files/images/EY-Global-Information-Security-Survey-2018.pdfGoogle Scholar
Vartanian, L. R., Herman, C. P., & Polivy, J. (2007). Consumption stereotypes and impression management: How you are what you eat. Appetite, 48(3), 265–277.CrossRefGoogle ScholarPubMed
Vishwanath, A., Harrison, B., & Ng, Y. J. (2018). Suspicion, cognition, and automaticity model of phishing susceptibility. Communication Research, 45(8), 1146–1166.CrossRefGoogle Scholar
Vogels, E. A. (2020, February). 10 facts about Americans and online dating. Pew Research Center. Retrieved from www.pewresearch.org/fact-tank/2020/02/06/10-facts-about-americans-and-online-dating/Google Scholar
Vosoughi, S., Roy, D., & Aral, S. (2018). The spread of true and false news online. Science, 359(6380), 1146–1151.CrossRefGoogle ScholarPubMed
Vraga, E. K., & Bode, L. (2020). Defining misinformation and understanding its bounded nature: Using expertise and evidence for describing misinformation. Political Communication, 37(1), 136–144.CrossRefGoogle Scholar
Vraga, E. K., Bode, L., & Tully, M. (2020). Creating news literacy messages to enhance expert corrections of misinformation on Twitter. Communication Research, 1–23.Google Scholar
Vrij, A. (2000). Detecting lies and deceit: The psychology of lying and implications for professional practice. Wiley.Google Scholar
Walther, J. B., & Parks, M. R. (2002). Cues filtered out, cues filtered in. Handbook of Interpersonal Communication, 3, 529–563.Google Scholar
Wang, J., Ipeirotis, P. G., & Provost, F. (2011, March). Managing crowdsourcing workers. In The 2011 Winter Conference on Business Intelligence (pp. 10–12).Google Scholar
Wang, Y., McKee, M., Torbica, A., & Stuckler, D. (2019). Systematic literature review on the spread of health-related misinformation on social media. Social Science & Medicine, 240, 112552.CrossRefGoogle ScholarPubMed
Wardle, C., & Derakhshan, H. (2017). Information disorder: Toward an interdisciplinary framework for research and policy making. Council of Europe Report, 1–107.Google Scholar
Waszak, P. M., Kasprzycka-Waszak, W., & Kubanek, A. (2018). The spread of medical fake news in social media – The pilot quantitative study. Health Policy and Technology, 7(2), 115–118.CrossRefGoogle Scholar
Wendling, M. (2017, April 2). Sandy Hook to Trump: “Help us stop conspiracy theorists.” BBC News. Retrieved from www.bbc.com/news/blogs-trending-39194035Google Scholar
Whitty, M. T. (2015). Anatomy of the online dating romance scam. Security Journal, 28(4), 443–455.CrossRefGoogle Scholar
Whitty, M. T., & Buchanan, T. (2012) The online romance scam: A serious cybercrime. Cyberpsychology, Behavior, and Social Networking, 15(3), 181–183.CrossRefGoogle ScholarPubMed
Whitty, M. T., Buchanan, T., Joinson, A. N., & Meredith, A. (2012). Not all lies are spontaneous: An examination of deception across different modes of communication. Journal of the American Society for Information Science and Technology, 63(1), 208–216.CrossRefGoogle Scholar
World Health Organization. (n.d.). Vaccines and immunization. World Health Organization. Retrieved from www.who.int/health-topics/vaccines-and-immunization#tab=tab_1Google Scholar
Worldwide Cancer Research. (2020, March). Could somebody be hiding the cure for cancer? Worldwide Cancer Research. Retrieved from www.worldwidecancerresearch.org/stories/2020/march/could-somebody-be-hiding-the-cure-for-cancer/Google Scholar
Xiao, B., & Benbasat, I. (2011). Product-related deception in e-commerce: A theoretical perspective. Mis Quarterly, 35(1), 169–196.CrossRefGoogle Scholar
Xie, S., Wang, G., Lin, S., & Yu, P. S. (2012, August). Review spam detection via temporal pattern discovery. In Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining (pp. 823–831). Association for Computing Machinery.Google Scholar
Yang, J., Xu, K., & Rodriguez, L. (2014). The rejection of science frames in the news coverage of the golden rice experiment in Hunan, China. Health, Risk & Society, 16(4), 339–354.CrossRefGoogle Scholar
Yang, K. C., Torres-Lugo, C., & Menczer, F. (2020). Prevalence of low-credibility information on Twitter during the COVID-19 outbreak. https://arxiv.org/abs/2004.14484Google Scholar
Yoo, K. H., & Gretzel, U. (2009). Comparison of deceptive and truthful travel reviews. In Information and Communication Technologies in Tourism, ENTER 2009, Proceedings of the International Conference in Amsterdam, The Netherlands (pp. 37-47). Springer.Google Scholar
Yuliani, S. Y., Sahib, S., Abdollah, M. F., Al-Mhiqani, M. N., & Atmadja, A. R. (2018). Review study of hoax email characteristic. International Journal of Engineering & Technology, 7(3.2), 778–782.Google Scholar
Zadrozny, B. (2019, October). Social media hosted a lot of fake health news this year. Here’s what went most viral. NBC News. Retrieved from www.nbcnews.com/news/us-news/social-media-hosted-lot-fake-health-news-year-here-s-n1107466Google Scholar
Zannettou, S., Sirivianos, M., Blackburn, J., & Kourtellis, N. (2019). The web of false information: Rumors, fake news, hoaxes, clickbait, and various other shenanigans. ACM Journal of Data and Information Quality, 11(3), 1–37.CrossRefGoogle Scholar
Zarei, K., Farahbakhsh, R., & Crespi, N. (2019, June). Deep dive on politician impersonating accounts in social media. In 2019 IEEE Symposium on Computers and Communications (ISCC) (pp. 1–6). IEEE.Google Scholar
Zarocostas, J. (2020). How to fight an infodemic. The Lancet, 395(10225), 676.CrossRefGoogle ScholarPubMed
Zenone, M., & Snyder, J. (2019). Fraud in medical crowdfunding: A typology of publicized cases and policy recommendations. Policy & Internet, 11(2), 215–234.CrossRefGoogle Scholar
Zhou, L., Burgoon, J. K., Nunamaker, J. F., & Twitchell, D. (2004). Automating linguistics-based cues for detecting deception in text-based asynchronous computer-mediated communications. Group Decision and Negotiation, 13(1), 81–106.CrossRefGoogle Scholar
Zielinska, O., Welk, A., Mayhorn, C. B., & Murphy-Hill, E. (2016, April). The persuasive phish: Examining the social psychological principles hidden in phishing emails. In Proceedings of the Symposium and Bootcamp on the Science of Security (pp. 126–126). Association for Computing Machinery.CrossRefGoogle Scholar
Zimbardo, P. G. (1969). The human choice: Individuation, reason, and order versus deindividuation, impulse, and chaos. In Nebraska Symposium on Motivation. University of Nebraska Press.Google Scholar
Zubiaga, A., & Ji, H. (2014). Tweet, but verify: Epistemic study of information verification on Twitter. Social Network Analysis and Mining, 4(1), 1–12.CrossRefGoogle Scholar
Zubiaga, A., & Jiang, A. (2020). Early detection of social media hoaxes at scale. ACM Transactions on the Web, 14(4), 1–23.CrossRefGoogle Scholar
Zywica, J., & Danowski, J. (2008). The faces of Facebookers: Investigating social enhancement and social compensation hypotheses; predicting Facebook™ and offline popularity from sociability and self-esteem, and mapping the meanings of popularity with semantic networks. Journal of Computer-Mediated Communication, 14(1), 1–34.CrossRefGoogle Scholar