Abstract
The ever-increasing use of telecommunication technologies and the Internet have led to an increase in new technology-facilitated types of crime and deviance. Due to the challenges posed by the unique environment of cyberspace on the formal crime control agents (e.g., the police), the role of informal guardians becomes particularly salient. The recent research suggests that informal guardianship against conventional crimes is common and that victims who are more socially active are more likely to receive help. However, it is not clear whether the same patterns of guardianship can be observed in cyberspace. To improve our understanding of how guardianship operates in cyberspace, the current study analyses the data from a sample of U.S. adults who were surveyed about their experiences with cyber abuse. The data was analyzed using mixed methods: a thematic analysis of open-ended responses, followed up by the logistic regression using Bayesian variable selection with the stochastic search algorithm. Our findings suggest that family, friends, intimate partners, authorities, work contacts, online friends, and netizens are most likely to provide guardianship. We also found that similar to conventional crimes like robbery or assault, the levels of guardianship responsibility are predictive of intervention against cyber abuse. Finally, we have established a link between the levels of regular interactions with various social groups and guardians’ availability and willingness to intervene. Implications for theory and practice, as well as future directions for research, are also discussed.
Similar content being viewed by others
Notes
Please note, estimates of prevalence of cyber abuse victimization vary from study to study ranging from as low as 6.5% of the sample in Dreßing et al. (2014) to 46% in Maran and Begotti (2019). The variation in prevalence is likely explained by the difference in how these studies defined, operationalized and measured the phenomenon under study (Kaur et al., 2021; Reyns, Henson, and Fisher, 2011a). Notably, most estimates of prevalence of cyber abuse are based on non-probability samples of college and university students; Pew Research Center study, which employed a large nationally-representative sample excluded (Vogels, 2021).
For example, in Vogels (2021), online harassment was measured using six distinct behaviours, including stalking: offensive name-calling; purposeful embarrassment; stalking; physical threats; harassment over a sustained period of time and sexual harassment. Reyns et al. (2011a, p. 101) cited the following examples of cyberstalking behaviours: “(1) continue to contact the victim after being asked to stop; (2) make unwanted sexual advances toward the victim; (3) impersonate or assume the victim’s identity with the intention of endangering the victim; and (4) persistently harass, annoy or threaten the victim to the point where the victim feels afraid for their safety”.
The survey was conducted in accordance with the ethical requirements of the Human Research Ethics Committee (HREC) of the host university and complied with ethics guidelines set forth by the HREC recommendations. Participants were informed that their data would be treated anonymously, no identifying information would be collected and they could withdraw from the survey at any time without providing a reason.
According to a longitudinal study by Difallah et al. (2018), MTurk has over 100,000 workers and around 2,000 active workers at any given time.
References
Abowitz, D., & Toole, T. (2010). Mixed method research: Fundamental issues of design, validity, and reliability in construction research. Journal of Construction Engineering and Management, 136(1), 108–116.
Alston-Knox, C. L. (2019). An intuitive guide to linear regression. Frequentist, Lasso and Bayesian Variable selection using AutoStat. Retrieved from https://autostat.com.au/resources.
Ando, T. (2010). Bayesian Model Selection and Statistical Modeling. Chapman and Hall, CRC, New-York. https://doi.org/10.1201/EBK1439836149
Axelrod, R., & Hamilton, W. D. (1981). The evolution of cooperation. Science, 211(4489), 1390–1396. https://doi.org/10.1126/science.7466396
Behrend, T. S., Sharek, D. J., Meade, A. W., & Wiebe, E. N. (2011). The viability of crowdsourcing for survey research. Behavior Research Methods, 43, 800–813.
Bocij, P. (2006). Cyberstalking: Harassment in the Internet age and how to protect your family. Praeger Publishers.
Bosch, O. J., Revilla, M., DeCastellarnau, A., & Weber, W. (2019). Measurement reliability, validity, and quality of slider versus radio button scales in an online probability-based panel in Norway. Social Science Computer Review, 37(1), 119–132.
Bossler, A. M., Holt, T. J., & May, D. C. (2012). Predicting online harassment victimization among juvenile population. Youth Society, 44, 500–523.
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101.
Broidy, L. (2001). A test of general strain theory. Criminology, 39, 9–35.
Casler, K., Bickel, L., & Hackett, E. (2013). Separate but equal? A comparison of participants and data gathered via Amazon’s MTurk, social media, and face-to-face behavioral testing. Computers in Human Behavior, 29(6), 2156–2160.
Clarke, R. V., & Eck, J. E. (2003). Become a problem-solving crime analyst: In 55 small steps. Jill Dando Institute of Crime Science, UCL.
Cohen, L. E., & Felson, M. (1979). Social change and crime rate trends: A routine activity approach. American Sociological Review, 44, 588–608.
Costello, M., Hawdon, J., & Ratliff, T. N. (2017). Confronting online extremism: The effect of self-help, collective efficacy, and guardianship on being a target for hate speech. Social Science Computer Review, 35(5), 587–605. https://doi.org/10.1177/0894439316666272
Difallah, D., Filatova, E., & Ipeirotis, P. (2018). Demographics and Dynamics of Mechanical Turk Workers. In Proceedings of the eleventh ACM international conference on web search and data mining (p. 135–143). New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3159652.3159661
Dressel, J., & Farid, H. (2018). The accuracy, fairness, and limits of predicting recidivism. Science Advances, 4(1).
Dreßing, H., Bailer, J., Anders, A., Wagner, H., & Gallas, C. (2014). Cyberstalking in a large sample of social network users: Prevalence, characteristics, and impact upon victims. Cyberpsychology, Behavior, and Social Networking, 17(2), 61–67. https://doi.org/10.1089/cyber.2012.0231
Enns, P. K., & Ramirez, M. (2018). Privatizing punishment: Testing theories of public support for private prison and immigration detention facilities. Criminology, 56, 546–573.
Felson, M., & Boba, R. (2010). Crime and everyday life: Insight and implications for society. Thousand Oaks, CA: Pine Forge.
Felson, M. (1995). Those who discourage crime. Crime and Place. Ed. by J. E. Eck and D. Weisburd. Monsey, NY: Criminal Justice Press, 53–66.
Fissel, E. R. (2018). The reporting and help-seeking behaviours of cyberstalking victims. Journal of Interpersonal Violence. https://doi.org/10.1177/0886260518801942
Gottlieb, A. (2017). The effect of message frames on public attitudes toward criminal justice reform for nonviolent offenses. Crime and Delinquency, 63, 636–656.
Grabosky, P., & Smith, R. (2001). Telecommunications fraud in the digital age: The convergence of technologies. Ed. by D. S. Wall, 10. London: Routledge, 243–249.
Hawdon, J., Costello, M., Ratliff, T., Hall, L., & Middleton, J. (2018). Conflict management styles and cybervictimization: Extending Routine Activity Theory. Sociological Spectrum, 37(4), 250–266. https://doi.org/10.1080/02732173.2017.1334608
Heinskou, M. B., & Liebst, L. S. (2017). Gadevold: En sociologisk kortlægning af vold i byen. Djøf Forlag.
Hoeting, J. A., Madigan, D., Raftery, A. E., & Volinsky, C. (1999). Bayesian model averaging: A tutorial. Statistical Science, 14(4), 382–401.
Hollis, M. E., Felson, M., & Welsh, B. C. (2013). The capable guardian in routine activities theory: A theoretical and conceptual reappraisal. Crime Prevention and Community Safety, 15(1), 65–79.
Hollis, M. E., & Welsh, B. C. (2014). What makes a guardian capable? A test of guardianship in action.Security Journal, 27.https://doi.org/10.1057/sj.2012.32
Hollis-Peel, M. E., Reynald, D. M., van Bavel, M., Elffers, H., & Welsh, B. C. (2011). Guardianship for crime prevention: A critical review of the literature. Crime, Law and Social Change, 56, 53–70.
Holt, T. J. (2010). Exploring strategies for qualitative criminological and criminal justice inquiry using online data. Journal of Criminal Justice Education, 21, 300–321.
Holt, T. J., & Bossler, A. M. (2008). Examining the applicability of lifestyle-routine activities theory for cybercrime victimization. Deviant Behaviour, 30, 1–25.
Ireland, L., et al. (2020). Preconditions for guardianship interventions in cyberbullying: Incident interpretation, collective and automated efficacy, and relative popularity of bullies. Computers in Human Behavior, 113, 106. https://doi.org/10.1016/j.chb.2020.106506
Jenaro, C., Flores, N., & Frias, C. P. (2018). Systematic review of empirical studies on cyberbullying in adults: What we know and what we should investigate. Aggression and Violent Behavior, 38, 113–122.
Jewkes, Y., & Yar, M. (2008). Policing Cybercrime: Emerging Trends and Future Challenges. Handbook of Policing. Ed. by T. Newburn. 2nd ed. Cullompton: Willan Publishing, 580– 606.
Jewkes, Y. (2010). Public policing and Internet crime. Handbook of Internet Crime. Ed. By Y. Jewkes and M. Yar. London: Willan, 525–545. https://doi.org/10.4324/9781843929338.
Kaur, P., Dhir, A., Tandon, A., Alzeiby, E. A., & Abohassan, A. A. (2021). A systematic literature review on cyberstalking. An analysis of past achievements and future promises. Technological Forecasting and Social Change, 163. https://doi.org/10.1016/j.techfore.2020.120426.
Kemp, S. (2019). Digital trends 2019: Every single stat you need to know about the internet. Retrieved from https://thenextweb.com/contributors/2019/01/30/digital-trends-2019-every-single-stat-you-need-to-know-about-the-internet/.
Krippendorff, K. (2013). Content analysis: An introduction to its methodology (3rd ed.). Sage.
Latane, B., & Darley, J. M. (1970). The unresponsive bystander: Why doesn’t he help. New York: NY: Appleton-Century-Crofts.
Latane, B., & Nida, S. (1981). Ten years of research on group size and helping. Psychological Bulletin, 89, 308–324.
Leukfeldt, E. (2014). Phishing for suitable targets in The Netherlands: Routine activity theory and phishing victimization. Cyberpsychology, Behavior and Social Networking, 17, 551–555. https://doi.org/10.1089/cyber.2014.0008
Leukfeldt, E., & Yar, M. (2016). Applying Routine Activity Theory to Cybercrime: A Theoretical and Empirical Analysis. Deviant Behavior, 37(3), 263–280. https://doi.org/10.1080/01639625.2015.1012409
Levay, K. E., Freese, J., & Druckman, J. N. (2016). The demographic and political composition of Mechanical Turk samples. SAGE Open, 1, 1–17.
Levine, M., & Manning, R. (2013). Social identity, group processes, and helping in emergencies. European Review of Social Psychology, 24(1), 225–251. https://doi.org/10.1080/10463283.2014.892318
Levine, M., Cassidy, C., & Brazier, G. (2006). Self-categorization and bystander non-intervention: Two experimental studies. Journal of Applied Social Psychology, 32, 1452–1463. https://doi.org/10.1111/j.1559-1816.2002.tb01446.x
Liebst, L. S., et al. (2019). Social relations and presence of others predict bystander intervention: Evidence from violent incidents captured on CCTV. Aggressive Behavior, 45(6), 598–609. https://doi.org/10.1002/ab.21853
Madigan, D., & Raftery, A. E. (1994). Model selection and accounting for model uncertainty in graphical models using Occam’s window. Journal of the American Statistical Association, 89, 1535–1546.
Maran, D. A., & Begotti, T. (2019). Prevalence of cyberstalking and previous offline victimization in a sample of Italian university students. Social Sciences, 8(1), 1–10. https://doi.org/10.3390/socsci8010030
Marcum, C. D., Rickets, M. L., & Higgins, G. E. (2010). Assessing sex differences of online victimization: An examination of adolescent online behaviors using routine activity theory. Criminal Justice Review, 35, 412–437.
Mawby, R. I. (1980). Witnessing Crime: Toward a Model of Public Intervention. Criminal Justice & Behavior, 7, 437–464.
McCullagh, P., & Nelder, J. (1989). Generalized Linear Models (2nd ed.). Chapman and Hall/CRC.
Miethe, T. D., & Meier, R. F. (1994). Crime and its social context: Toward an integrated theory of offenders, victims, and situations. State University of New York Press.
Ngo, F. T., & Paternoster, R. (2011). Cybercrime victimization: An examination of individual and situational level factors. International Journal of Cyber Criminology, 3, 773–793.
Parsons-Pollard, N., & Moriarty, L. J. (2009). Cyberstalking: Utilizing What We Do Know. Victims & Offenders, 4(4), 435–441.
Phillips, F., & Morrisey, G. (2004). Cyberstalking and cyberpredators: A threat to safe sexuality on the Internet. Convergence, 10, 66–79.
Philpot, R., Liebst, L. S., Levine, M., Bernasco, W., & Lindegaard, M. R. (2019). Would I be helped? Cross-national CCTV footage shows that intervention is the norm in public conflicts. The American psychologist, 75.https://doi.org/10.1037/amp0000469
Raftery, A. (1995). Bayesian model selection in social research. Sociological Methodology, 25, 111–163.
Reynald, D. M. (2009). Guardianship in action: Developing a new tool for measurement. Crime Prevention and Community Safety, 11(1), 1–20.
Reynald, D. M. (2010). Guardians on guardianship: Factors affecting the willingness to monitor, the ability to detect potential offenders and the willingness to intervene. Journal of Research in Crime and Delinquency, 47(3), 358–390.
Reynald, D. M. (2011). Factors associated with the guardianship of places: Assessing the relative importance of the spatio-physical and sociodemographic contexts in generating opportunities for capable guardianship. Journal of Research in Crime and Delinquency, 48(1), 110–142. https://doi.org/10.1177/0022427810384138
Reynald, D. M. (2014). Informal guardianship. Encyclopedia of Criminology and Criminal Justice. Ed. By G. Bruinsma and D. Weisburd. Springer, New York, NY, 2480–2489.
Reynald, D. M. (2018). Guardianship and informal social control. Oxford Research Encyclopedia of Criminology. Retrieved from . https://www.oxfordre.com/criminology/view/10.1093/acrefore/9780190264079.001.0001/acrefore-9780190264079-e-315
Reyns, B. W., Henson, B., & Fisher, B. S. (2011a). A situational crime prevention approach to cyberstalking victimization: Preventive tactics for Internet users and online place managers. Crime Prevention and Community Safety, 12(2), 99–118.
Reyns, B. W., Henson, B., & Fisher, B. S. (2011b). Being pursued online: Applying cyberlifestyle routine activities theory to cyberstalking victimization. Criminal Justice and Behaviour, 38, 1149–1169.
Reyns, B. W., Fisher, B. S., & Randa, R. (2018). Explaining Cyberstalking Victimization Against College Women Using a Multitheoretical Approach: Self-Control, Opportunity, and Control Balance. Crime & Delinquency, 64(13), 1742–1764. https://doi.org/10.1177/0011128717753116
Reyns, B. W., Henson, B., & Fisher, B. S. (2016). Guardians of the cyber galaxy: An empirical and theoretical analysis of the guardianship concept from routine activity theory as it applies to online forms of victimization. Journal of Contemporary Criminal Justice, 1–21.
Roberts, P., Priest, H., & Traynor, M. (2006). Reliability and validity in research. Nursing Standard, 20, 41–45. https://doi.org/10.7748/ns.20.44.41.s56
Sampson, R. J., Raudenbush, S. W., & Earls, F. (1997). Neighborhoods and Violent Crime: A Multilevel Study of Collective Efficacy. Science, 277(5328), 918–924. https://doi.org/10.1126/science.277.5328.918
Slater, M., et al. (2013). Bystander Responses to a Violent Incident in an Immersive Virtual Environment. PLoS ONE, 8(1), 1–13. https://doi.org/10.1371/journal.pone.0052766
Swann, W. B., & Jetten, J. (2017). Restoring Agency to the Human Actor. Perspectives on Psychological Science, 12(3), 382–399. https://doi.org/10.1177/1745691616679464
Tewksbury, R., & Mustaine, E. E. (2003). College students’ lifestyles and self-protective behaviours: Further considerations of the guardianship concept in routine activity theory. Criminal Justice and Behaviour, 30, 302–327.
U.S. Census Bureau Quick facts. (2018). Retrieved from https://www.census.gov/quickfacts/fact/table/US/ PST045217.
V´azquez, A., Gómez, Á., Ordoñana, J. R., Swann, W. B., & Whitehouse, H. (2017). Sharing genes fosters identity fusion and altruism. Self and Identity, 16, 684–702.https://doi.org/10.1080/15298868.2017.1296887
Vakhitova, Z. I., & Reynald, D. M. (2014). Australian Internet users and guardianship against cyber abuse: An empirical analysis. International Journal of Cyber Criminology, 8(2), 156–171.
Vakhitova, Z. I., Reynald, D. M., & Townsley, M. K. (2016). Toward adapting routine activity and lifestyle exposure theories to account for cyber abuse victimization. Journal of Contemporary Criminal Justice, 32(2), 169–188.
Vakhitova, Z. I., Alston-Knox, C. L., Reynald, D. M., Townsley, M. K., & Webster, J. L. (2019). Lifestyles and routine activities: Do they enable different types of cyber abuse? Computers in Human Behaviour, 101, 225–237.
Vakhitova, Z. I., & Alston-Knox, C. L. (2018). Non-significant p-values? Strategies to understand and better determine the importance of effects and interactions in logistic regression. PLoS ONE,13(11). https://doi.org/10.1007/s10940-010-9106-6 .
Vakhitova, Z. I., Mawby, R. I., Alston-Knox, C. L., & Stephens, C. A. (2020). To SPB or not to SPB? A mixed methods analysis of self-protective behaviours to prevent repeat victimisation from cyber abuse. Crime Science, 19(24).
Vaughan, T. J., Holleran, L. B., & Silver, J. (2019). Applying moral foundations theory to the explanation of capital jurors’ sentencing decisions. Justice Quarterly, 36(7), 1176–1205. https://doi.org/10.1080/07418825.2018.1537400
Vogels, E. (2021). Online harassment. Retrieved from https://www.pewresearch.org/internet/2021/01/13/the-state-of-online-harassment/
Weinberg, J. D., Freese, J., & McElhattan, D. (2014). Comparing data characteristics and results of an online factorial survey between a population-based and a crowdsource-recruited sample. Sociological Science, 1, 292–310.
Wickes, R., Hipp, J., Sargeant, E., & Mazerolle, L. (2017). Neighborhood social ties and shared expectations for informal social control: Do they influence informal social control actions? Journal of Quantitative Criminology, 33, 101–129. https://doi.org/10.1007/s10940-016-9285-x
Wilcox, P., Jordan, C. E., & Pritchard, A. J. (2007). A multidimensional examination of campus safety: Victimization, perceptions of danger, worry about crime, and precautionary behavior among college women in the post-Clery era. Crime & Delinquency, 53, 219–254.
Williams, M. L. (2015). Guardians upon high: An application of routine activities theory to online identity theft in Europe at the country and individual level. The British Journal of Criminology, 56(1), 21–48. https://doi.org/10.1093/bjc/azv011
Yar, M. (2005). The novelty of cybercrime. European Journal of Criminology, 2, 407–427.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Vakhitova, Z.I., Go, A. & Alston-Knox, C.L. Guardians Against Cyber Abuse: Who are They and Why do They Intervene?. Am J Crim Just 48, 96–122 (2023). https://doi.org/10.1007/s12103-021-09641-w
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12103-021-09641-w