Abstract
This study stands out from previous studies because it classifies Internet users into the following four groups: users who experienced no deviant behavior in cyberspace, users who suffered damage by it, perpetrators of deviant behavior, and users who experienced both wrongdoing and damage. Data from the 2016 Survey on the Digital Divide were used to examine the relationships between experiences of deviant behavior in cyberspace and emotional states (depression, anxiety, loneliness, and self-esteem). The results found that males were more likely than females to experience wrongdoing and damage. Teenagers and those aged 20–29 were relatively more likely to experience both types of deviant behavior in cyberspace and to be perpetrators. The differences in Internet literacy and smart literacy by type of deviant behavior were all statistically significant. Although there were no significant differences in loneliness or anxiety by group, depression and self-esteem were statistically different among the four groups.
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Data Availability
The data used in this study are publicly available from the National Information Society Agency (https://www.nia.or.kr/site/nia_kor/main.do) and OSF (https://osf.io/57arp).
References
Adams, C. (2010). Cyberbullying: How to make it stop. Instructor, 120(2), 44–49.
Agnew, R. (1992). Foundation for a general strain theory of crime & delinquency. Criminology, 30, 47–87.
Agnew, R. (2006). Pressured into crime: an overview of general strain theory. Roxbury.
Ah, Y. A., & Jang, W. C. (2012). Mediating effects of internet addiction in the relationship between school violence aggression and victimization. Korean Journal of Youth Studies, 19(12), 331–354.
Arnklev, B. J., Grasmick, H. G., Tittle, C. R., Bursik, R. J., & Hr. . (1993). Low self-control and imprudent behavior. Journal of Quantitative Criminology, 9, 225–247.
Baron, S. (2004). General strain, street youth, and crime: A Test of Agnew’s revised strain theory. Criminology, 42, 457–483.
Bouhnik, D., & Deshen, M. (2013). Unethical behavior of youth in the internet environment. The International Journal of Technology, Knowledge, and Society, 9(2), 109–124. https://doi.org/10.18848/1832-3669/CGP/v09i02/56372
Broidy, L. M. (2001). A test of general strain theory. Criminology, 39, 9–35. https://doi.org/10.1111/j.1745-9125.2001.tb00915.x
Broidy, L. M., & Agnew, R. (1997). Gender and crime: A general strain theory perspective. Journal of Research in Crime and Delinquency, 34, 275–306.
Caplan, S. E. (2003). Preference of online social interaction: A theory of problematic internet use and psychosocial well-being. Communication Research, 30(6), 625–648. https://doi.org/10.1177/0093650203257842
Chapell, M. S., Hasselman, S. L., Kitchin, T., Lomon, S. N., MacIver, K. W., & Sarullo, P. L. (2006). Bullying in elementary school, high school, and college. Adolescence, 41, 633–648.
Cho, C. H., & Cheon, H. J. (2005). Children’s exposure to negative Internet content: Effects of family context. Journal of Broadcasting & Electronic Media, 49(4), 488–509.
Cho, Y. O. (2012). A study on the probation-police partnerships in preventing school violence. Correction Review, 55, 55–77.
Choo, B. W. (2005). Systematization of Information Ethics Education, Seoul: Korea Internet Safety Commission
Cohen, E. G., & Farrington, D. P. (1999). Changes in the most-cited scholars in twenty criminology and criminal justice journal of between 1990 and 1995. Journal of Criminal Justice, 27, 345–359. https://doi.org/10.1016/S0047-2352(99)00006-9
Davis, R. A. (2001). A Cognitive-Behavioral Model of Pathological Internet Use. Computers in Human Behavior, 17, 187–195. https://doi.org/10.1016/S0747-5632(00)00041-8
Evan, T. D., Cullen, F. T., Burton, V. S. J., Dunaway, R. G., & Benson, M. L. (1997). The social consequences of self-control: Testing the general theory of crime. Criminology, 35, 475–502. https://doi.org/10.1111/j.1745-9125.19973.tb01226.x
Gámez-Guadix, M., Orue, I., Smith, P. K., & Calvete, E. (2013). Longitudinal and reciprocal relations of cyberbullying with depression, substance use, and problematic internet use among adolescents. Journal of Adolescent Health, 53, 446–452. https://doi.org/10.1016/j.jadohealth.2013.03.030
Gibbs, J. J., & Giever, D. (1995). Self-control and its manifestations among university students: An empirical test of Gottfredson and Hirschi’s general theory. Justice Quarterly, 12, 231–155. https://doi.org/10.1080/07418829500092661
Goebert, D., Else, I., Matsu, C., Chung-Do, J., & Chang, J. Y. (2011). The impact of cyberbullying on substance use and mental health in a multiethnic sample. Maternal and Child Health Journal, 15, 1282–1286. https://doi.org/10.1007/s10995-010-06872-x
Grasmick, H. G., Tittle, C. R., Bursik, R. J., Jr., & Arnekelv, B. J. (1993). Testing the core empirical implication of Gottfredson and Hirshi’s general theory of crime. Journal of Research in Crime and Delinquency, 30, 5–29. https://doi.org/10.1177/0022427893030001002
Hay, C., & Evans, M. (2006). Violent victimization and involvement in delinquency: Examining predictions from general strain theory. Journal of Criminal Justice, 34, 261–274. https://doi.org/10.1016/j/jcrimjus.2006.03.005
Hinduja, S., & Patchin, J. W. (2007). Cyberbullying: An exploratory analysis of factors related to offending and victimization. Deviant Behavior, 35, 129–156. https://doi.org/10.1080/0163962070147816
Holt, T., & Bossler, A. (2009). Examining the applicability of lifestyle routine activities theory for cybercrime victimization. Deviant Behavior, 30, 1–25. https://doi.org/10.1080/01639620701876577
International Telecommunication Union (2017). Measuring the Information Society Report. Retrieved from http://handle.itu.int/11.1002/pub/80f52533-en.
Jeong, H. K., & Chol, T. J. (2013). Characteristics of communication according to the middle school students’ school violence experience types. Korea Journal of Counseling., 14(1), 573–591.
Jun, S., & Lee, S. (2010). Exploring explanatory factors for youth’s cyber-bullying by cell phone. Korean Journal of Youth Studies, 17(11), 159–181.
Jung, H. (2009). A study of social bonding, self-control, and opportunity theories on the persistent cyber delinquency. The Korea Journal of Information Policy, 16(4), 97–112.
Kim, D. I., Lee, Y. H., Kang, M. C., & Chung, Y. J. (2013). A multi-level meta analysis on the relations between mental health problems and internet addiction. Korean Journal of Counseling, 14(1), 285–303.
Kim, G. J., & Suh, S. H. (2006). The research on a path-model on adolescent’s psychological․ Environmental variables affecting the internet addiction. Studies on Korean Youth, 17(1), 149–179.
Kim, H. H. (2003). The effect of maternal monitoring and psychological control on problem behavior and internet delinquency in adolescence. Korean Journal of Youth Studies, 10(3), 133–153.
Kim, K., & Yoon, H. (2012). Influences of eco-systemic factors related to adolescents’ cyber violence. Journal of Youth Welfare, 14(1), 213–238.
Kim, S. J. (2005). Psychological and social factors influencing bullying and victim tendencies. The Korea Journal of Counselling, 6(2), 359–371.
Kim, S. W., & Kim, T. H. (2011). Relationship between family, school, internet, use environmental factors and middle school students’ internet dependence: Inspecting mediation effect of depression. Korean Journal of Family Relations, 15(4), 25–49.
Kim, Y-H. (2016). Social media use tendency and behavior. KISDISTAT REPORT, 16.
Korea Internet Safety Commission (2003). White Paper for Information Ethics. Seoul
Kowalski, R. M., & Limber, S. P. (2013). Psychological, physical, and academic correlates of cyberbullying and traditional bullying. Journal of Adolescent Health, 53, S13–S20. https://doi.org/10.1016/j.jadohealth.2012.09.018
Kowalski, R. M., Limber, S. P., & Agatston, P. W. (2008). Cyberbullying. Blackwell.
Kraut, R., Patterson, M., Lundmark, V., Kiesler, S., Mukophadhyay, T., & Scherlis, W. (1998). Internet paradox: A social technology that reduces social movement and psychological well-being? American Psychologists, 53, 1017–1031.
Landsheer, J. A., & Van Dijkum, C. (2005). Male and female delinquency trajectories from pre through middle adolescence and their continuation in late adolescence. Adolescence, 40, 729–748.
Lau, W. W. F., & Yuen, A. H. K. (2013). Internet ethics of adolescents: Understanding demographic differences. Computer & Education, 72, 378–385. https://doi.org/10.1016/j.compedu.2013.12.006
Lee, D. S. (2003). Relationship between adolescent internet addiction and depression and self-identity, (Unpublished doctoral dissertation). Cheon Nam University.
Lee, H. (2010). What makes people do unethical behaviors in the online environment?-focused on digital contents usage. Journal of Consumer Policy Studies, 38, 1–19.
Lee, J., & Woo, H. (2010). A study on the intention toward cyber verbal bullying: Focusing on the perception to cyber libel/insult, age and the variables of the theory of planned behavior. Journal of Cybercommunication Academic Society, 27(1), 215–253.
Lee, S. J., & Bae, K. H. (2004). A comparison of self-esteem, aggression, and depression between the adolescent group of internet abuse and adolescent group of the internet normal use. Korean Journal of Youth Studies, 11(3), 299–319.
Lee, S. S. (2004). Strain, negative emotions, and cyber-delinquency: Testing a gender difference. Korean Academy of Public Safety and Criminal Justice, 18, 273–299.
Lee, S. S., & Jeon, S. H. (2012). Internet usage, strain, and delinquency: Analyzing youth panel data. Criminal Policy Studies, 23(3), 293–318.
Marcum, C. D., Higgins, G. E., & Ricketts, M. L. (2010). Potential factors of online victimization of youth: An examination of adolescent online behaviors utilizing routine activity theory. Deviant Behavior., 31, 381–410. https://doi.org/10.1080/01639620903004903
Moon, B., Blurton, D., & McKluskey, J. D. (2008). General strain theory and delinquency: Focusing on the influences of key strain characteristics on delinquency. Crime and Delinquency, 54, 584–613. https://doi.org/10.1177/0011128707301627
Morahan-Martin, J., & Schumacher, P. (2000). Incidence and correlates of pathological internet use among college students. Computers in Human Behavior, 16, 13–29.
Nam, S.-J. (2019). Mediating effect of social support on the relationship between older adults’ use of social media and their quality-of-life. Current Psychology. https://doi.org/10.1007/s12144-019-00399-3
Nam, S. J. (2017). Who behaves unethically on the internet? An Examination of the effects of online ethical sensitivity and internet use patterns. Transylvanian Review, 24(16), 3571–3582.
Nam, Y. Y. (2005). Comparison of internet addiction, internet game addiction and cybersex addiction among middle school students. Korean Journal of Youth Studies, 12(3), 363–388.
Oh, E. J. (2010). Cyberbullying among middle school students. Journal of Korean Adolescent Culture, 15, 219–243.
Oh, J., & Ah, Y. A. (2006). The factors effecting on experiencing both aggression and victimization of school violence. Journal of Social Welfare Development, 12(1), 79–100.
Olweus, D. (1978). Aggression in the school: Bullies and shipping boys. Hemisphere Press.
Osgood, D. W., Wilson, J. K., O’Malley, P. M., Bachman, J. G., & Johnston, L. D. (1996). Routine activities and individual deviant behavior. American Sociological Review, 61, 635–655.
Park, H., & Jung, H. (2018). The factors affecting juvenile cyber verbal violence among adolescents. Studies on Korean Youth, 29(2), 217–240.
Park, M. C. (2012). A study on the approach model of adolescent’s internet addiction. Korean Association of Addiction Crime Review, 2(1), 1–12.
Park, S. J. (2006). Developing patterns of victim-offending experiences in adolescent violence. Criminal Policy Studies, 17(1), 47–88.
Patchin, J, W., & Hinduja, S. (2011). Traditional and nontraditional bullying among youth: a test of general strain theory. Youth & Society, 43(2), 727-751. https://doi.org/10.1177/0044118X10366951
Piquero, N. L., & Sealock, M. D. (2000). Generalizing general strain theory: An examination of an offending population. Justice Quarterly, 17, 449–484.
Piquero, N. L., & Sealock, M. D. (2004). Gender and general strain theory: A preliminary test of Broidy and Agnew’s gender/GST hypotheses. Justice Quarterly, 21, 125–159.
Polakwski, M. (1994). Linking self-and social control with deviance: Illumination the structure underlying a general theory of crime and its relation to deviant activity. Journal of Quantitative Criminology, 10, 41–78. https://doi.org/10.1007/BF02221008
Reyns, B. W., Henson, B., & Fisher, B. S. (2011). Being pursued online: Applying cyber lifestyle-routine activities theory to cyberstalking victimization. Criminal Justice and Behavior, 38, 1149–1169. https://doi.org/10.1177/0093854811421448
Rigby, K. (2008). Children and bullying: How parents and educators can reduce bullying at school. Blackwell.
Shin, H. S. (2005). Effect of individual, family, and peer and school variables on the middle school students’ peer violence type. Korean Journal of Youth Studies, 12(4), 123–149.
Sung, D. K., Kim, D. H., Lee, Y. S., & Lim, S. W. (2006). A study on the cyber-violence induction factors of teenagers: Focused on individual inclination, cyber violence damage experience, and moral consciousness. Korea Journal of Cyber Communication, 19, 79–129.
Tokunaga, R. (2010). Following you home from school: A critical review and synthesis of research on cyberbullying victimization. Computer in Human Behavior, 26, 277–287. https://doi.org/10.1016/j.chb.2009.11.014
Wang, J., Nansel, T. R., & Iannotti, R. J. (2011). Cyber and traditional bullying: Differential association depression. Journal of Adolescent Health, 48, 415–417. https://doi.org/10.1016/j.jadohelath.2010.07.012
Williams, K. D., Cheung, C. K. T., & Choi, W. (2000). Cyberostracism: Effects of being ignored over the internet. Journal of Personality and Social Psychology, 79, 748–762.
Williams, K., Harkins, S., & Latane, B. (1981). Identifiability as a deterrent to social loafing: Two cheering experiments. Journal of Personality and Social Psychology, 40, 303–311.
Wolfe, S. E., & Higgins, G. E. (2009). Explaining deviant peer associations: An examination of low self-control, ethical predispositions, definitions, and digital piracy. Western Criminology Review, 10(1), 43–55.
Woo, H. J. (2007). A study on the influence of mobile phone users' self-traits on mobile phone addiction - focusing on self-esteem, self-efficacy, and self-control. Korean Journal of Broadcasting and Telecommunication Studies, 21(2), 391∼427.
Woo, H. J., & Lee, J. K. (2012). A Study on the internet pornograph immersion and addiction affected by the level and security of self-esteem. Journalism & Communication, 16(3), 55–84.
Wood, P. B., Pfefferbaum, B., & Arneklev, B. J. (1993). Risk-taking and self-control: Social psychological correlation of delinquency. Journal of Crime and Justice, 16, 111–130. https://doi.org/10.1080/0735648X31993.9721481
Yang, D. K. (2000). The relationships between adolescent’s sensation seeking, internet addiction tendency, and internet-related delinquency. Korean Journal of Youth Studies, 17(2), 117–136.
Young, K. S. (1998). Caught in the net: How to recognize the signs of internet addiction and a wigs strategic for recovery. John Wiley & Sons INC.
Young, K. S. (1997). The Relationship between Depression and Internet Addiction. Cyberpsychology and Behavior, 1, 25–28.
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Nam, SJ. Deviant behavior in cyberspace and emotional states. Curr Psychol 42, 10751–10760 (2023). https://doi.org/10.1007/s12144-021-02370-7
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DOI: https://doi.org/10.1007/s12144-021-02370-7