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IJERPHInternational Journal of Environmental Research and Public Health
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28 June 2020

A Study on the Cause Analysis of Cyberbullying in Korean Adolescents

Department of Computer Education, Seoul National University of Education, Seoul 06639, Korea
Int. J. Environ. Res. Public Health2020, 17(13), 4648;https://doi.org/10.3390/ijerph17134648
This article belongs to the Special Issue Cyber-Victimization Prevention among Adolescents
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Abstract

With the development of information and communication technology, online communication is becoming more active than offline meetings in daily life. This online communication is accelerating, especially as smartphone distribution and utilization become more prevalent. This communication in cyberspace has the advantage of people being able to communicate anytime, anywhere beyond time and place, while causing a variety of inappropriate consequences. A typical one is cyberbullying, which is a serious problem for adolescents who have active communication online. The purpose of this study is to accurately investigate and analyze the status of cyberbullying among adolescents. To this end, national survey data of the National Information Society Agency (NIA) was analyzed for the past three years. The population size and sample size from 2017 to 2019 were 5.773.998 and 4500 (2017), 5,663,725 and 4662 (2018), 5,502,801 and 4779 (2019), respectively. The statistical analysis shows that the biggest type of cyberbullying among adolescents is verbal abuse, and the biggest means is instant messaging. In addition, the most frequent forms of cyberbullying victims and cyberbullying perpetrators occur between individuals. In addition, the correlation between the interpersonal relationships of adolescents and the cyberbullying experience rate were analyzed, and various cyberbullying factors such as psychological factors were analyzed. As a result, we found that the interaction with parents and friendship reliability have a negative correlation with the cyberbullying experience rate. We expect the results of this study to be of great help to future research and policies of juvenile cyberbullying.

1. Introduction

Modern society is a knowledge information society, and the core technologies of a knowledge information society are smart technology, information technology, and communication technology. Smart technology aims to simulate a system by giving sensing, control, and computation functions to mechanical, aeronautical, and civil structures so that they can detect changes in their surroundings and respond to information in real-time [1]. On the other hand, information and communication technology (ICT) is “an extensional term for information technology (IT) that stresses the role of unified communications and the integration of telecommunications and computers, as well as necessary enterprise software, middleware, storage, and audiovisual systems that enable users to access, store, transmit, and manipulate information” [2].
Smart technology, along with information and communication technology, provided abundant benefits to our lives in a modern knowledge and information society. Among the various benefits of information and communication technology, online communication is especially a very convenient benefit. In other words, offline meetings are limited in time and place, but online meetings in virtual space can transcend time and place, giving and receiving real-time feedback anytime, anywhere. This online communication not only allows individuals to communicate actively, but also causes socially active communication, which has the advantage of being able to inform adolescents quickly in case of an emergency, such as an earthquake, and also to quickly gather various opinions on school life issues.
However, while information and communication technology provides us with various benefits, it also causes various negative impacts. Among the various negative impacts, cyberbullying is a typical one, causing us not only mental but also social and economic problems. Especially for adolescents, whose values and personalities have not been established yet, deviations from cyberspace cause a number of problems, including emotional problems and academic interference. With the popularization of smartphones, adolescents increasingly own and use smartphones. Thus, cyberbullying can be a more serious social phenomenon in the future for adolescents, and it requires proper prevention and treatment.
The purpose of this study is to investigate and analyze the cyberbullying status of adolescents. Specifically, the purpose of this study is to analyze the occurrence process, along with the causes of cyberbullying among adolescents. In order to do this, it is necessary to investigate and analyze the cyberbullying status of various adolescents correctly, accurately, and objectively. These vast surveys require a lot of time and effort, and there should be proper questionnaires that are done as fairly as possible.
In this study, we decided to use the nation-level cyberbullying survey reports to analyze the cyberbullying status of adolescents as fairly and objectively as possible. Since 2014, the National Information Society Agency (NIA, http://www.nia.or.kr) has conducted a comprehensive and systematic survey of cyberbullying and analyzed the results statistically [3,4,5]. In addition, NIA has conducted and published a survey on the public’s internet use [6,7,8,9,10,11,12,13,14,15,16,17]. The study analyzed the cyberbullying status of adolescents based on cyberbullying reports for three years from 2017 to 2019. The population size and sample size from 2017 to 2019 were 5.773.998 and 4500 (2017), 5,663,725 and 4662 (2018), 5,502,801 and 4779 (2019), respectively. The purpose of using the statistics for the last three years is to include the most recent statistics, which are different from previous years’ questionnaires. In this work, adolescents include elementary school students, middle school students, and high school students, respectively.
In this study, based on the survey results, we show whether the following three hypotheses are correct or not.
Hypothesis 1 (H1).
The most common type of cyberbullying is verbal violence.
Hypothesis 2 (H2).
The most common means of cyberbullying is instant messaging.
Hypothesis 3 (H3).
The most common form of cyberbullying occurs between individuals.

3. Statistical Analysis of Cyberbullying in Adolescents

In this section, we present various statistical analyses on cyberbullying of adolescents in Korea as follows.

3.1. Analysis Methods

The purpose of the statistical analysis is to identify the various causes of cyberbullying in adolescents. In this study, we would like to find out the following specific conditions regarding the cyberbullying causes of adolescents. First, it is about the type of cyberbullying. Second, it is about the means of cyberbullying. In other words, we look at the means of communication through which cyberbullying occurs. Third, it is to find out whether cyberbullying occurs between groups or between individuals.
For the statistical analysis of this work, we adopted nationwide statistical data from the National Information Society Agency (http://www.nia.or.kr) [3,4,5]. The agency has announced cyberbullying statistics since 2014. Samples of this survey have been collected evenly throughout the country. The survey results since 2017 were analyzed using the Statistical Package for the Social Sciences (SPSS) WIN 25.0 program (IBM, Armonk, NY, USA). One-way ANOVAs and t-tests were conducted to find out the type, means and forms of cyberbullying by adolescents. Note that the survey method before 2017 was different from the survey method after 2017, so data before 2017 was not adopted.
The purpose of the national cyberbullying survey by NIA is to identify the status of cyber violence and the level of instructional education through quantitative investigation and to secure in-depth evidence, such as cases by type of cyber violence, through qualitative investigation. The survey was conducted as follows. In this paper, we introduce the most recent data of 2019 since the survey was carried out for the rest of the year in a similar way. First, the survey period was about six weeks, from 1 October to 23 November 2019. In addition, 4779 samples were selected from a population of about 5.5 million, and data were collected through mail, internet surveys (quantitative surveys), and collective interviews (qualitative surveys). Meanwhile, sampling methods were used for a stratified extraction method (quantitative survey) and random sampling (qualitative survey). The sample error (95% confidence level) was ±1.42% p. The survey items included internet usage behavior, cyber victimization experience, cyberbullying experience, cyberbullying witness experience, and social and psychological environment factors.

3.2. Cyberbullying Survey Data

The cyberbullying status of adolescents based on the National Information Society Agency [3,4,5] is summarized as follows.
First, the following Table 1 and Table 2 show the cyberbullying status of adolescents by type.
Table 1. Cyberbullying status of adolescents by type of cyberbullying.
Table 2. Cyberbullying status of adolescents by type of cyber victimization.
The following Table 3 and Table 4 show the cyberbullying status of adolescents by means.
Table 3. Cyberbullying status of adolescents by means of cyberbullying.
Table 4. Cyberbullying status of adolescents by means of cyber victimization.
The following Table 5 and Table 6 show the cyberbullying status of adolescents by forms.
Table 5. Cyberbullying status of adolescents by means of cyberbullying.
Table 6. Cyberbullying status of adolescents by means of cyber victimization.
As we can see from Table 1 and Table 2, in the cyberbullying of adolescents, the most common type of violence is verbal violence. Moreover, from Table 3 and Table 4, we can see that the most common means of violence is instant messaging. From Table 5 and Table 6, we can see that the most common form of violence occurs between individuals.

3.3. Statistical Analysis Results

The results of the statistical analysis for cyberbullying type are shown in Table 7.
Table 7. Summary of statistical analysis for cyberbullying type.
As shown in Table 7, the average value of each type of cyberbullying is as follows. Verbal violence is the highest at 16.90, followed by defamation 4.80, stalking 2.33, personal information leakage 2.25, ostracism 1.80, sexual violence 1.72, extortion 1.20, and coercion 0.87. The statistically significant difference is F = 188.38, p < 0.001. Therefore, we can conclude that the biggest type of cyberbullying among adolescents is verbal violence.
In addition, the results of statistical analysis for cyberbullying means are shown in Table 8.
Table 8. Summary of statistical analysis for cyberbullying means.
As shown in Table 8, the average value for cyberbullying means is as follows. Instant messages are the highest at 48.62, followed by online games 39.50, SNS 30.47, community 4.00, email/text 2.52, and personal homepage 2.08. The statistically significant difference is F = 259.14; p < 0.001. Therefore, the biggest means of cyberbullying among adolescents is instant messaging.
Finally, the results of statistical analysis for cyberbullying forms are shown in Table 9.
Table 9. Summary of statistical analysis for cyberbullying forms.
As shown in Table 9, the mean for person-to-person violence is 73.88, higher than the 25.62 mean for group-to-person violence (t = 28.26, p < 0.001). Thus, it is shown that cyberbullying among adolescents occurs more in a person-to-person fashion than in a group-to-person manner.

3.4. Nonparametric Statistical Analysis Results

This section introduces the results of applying nonparametric statistical methods to analyze survey data in various ways. In this study, Kruskal–Wallis H verification and Mann–Whitney U verification were performed among nonparametric statistical techniques.
The results of statistical analysis for cyberbullying type are shown in Table 10.
Table 10. Summary of statistical analysis for cyberbullying type (nonparametric case).
As shown in Table 10, verbal violence is the highest among the types of cyberbullying with 45.50, followed by defamation with 39.17, personal information leakage with 28.00, stalking with 26.00, ostracism with 20.17, sexual violence with 18.50, extortion with 10.50, and coercion with 8.17. There is a significant difference in statistics (Χ2 = 36.48, p < 0.001). Therefore, it can be seen that the most common type of cyberbullying among adolescents is verbal violence.
Additionally, the results of statistical analysis for cyberbullying means are shown in Table 11.
Table 11. Summary of statistical analysis for cyberbullying means (nonparametric case).
As shown in Table 11, instant messaging tops the list of cyber-bullying means with 33.50, followed by online gaming 27.50, SNS 21.50, community 13.00, email/text 8.42, and personal homepages 7.08, showing a statistically significant difference (Χ2 = 31.24, p < 0.001). Therefore, it can be seen that the most common means of cyberbullying among adolescents is instant messaging.
Finally, the results of statistical analysis for cyberbullying forms are shown in Table 12.
Table 12. Summary of statistical analysis for cyberbullying forms (nonparametric case).
As shown in Table 12, the average ranking is 9.50 for person-to-person violence, which is higher than 3.50 for group-to-person violence, with a statistically significant difference (Z = -2.88 and p < 0.01). Therefore, it can be seen that cyberbullying among adolescents occurs more in a person-to-person way than in a group-to-person way.

3.5. Correlation Analysis of Parent and Friend Relationships

In this section, to analyze the various causes of adolescent cyberbullying, the factors of parent and friend relationships are analyzed. To this end, the latest adolescent cyberbullying status report [3] is used to analyze three factors as follows.
  • The relationship between parents’ involvement in internet use and their children’s cyberbullying experience rate.
  • The relationship between parents’ and children’s interaction with their children’s cyberbullying experience rate.
  • The relationship between friend relationship reliability and the adolescents’ cyberbullying experience rate.
The collected data in [3] were analyzed using the SPSS WIN 25.0 program. Correlation analysis was conducted to find out the relationship between the adolescent cyberbullying experience rate and the three factors.
Table 13, Table 14 and Table 15 show the parents’ involvement in internet use and their children’s cyberbullying experience rate, the interaction between parents and children and their children’s cyberbullying experience rate, and the reliability of friend relationships and the cyberbullying experience rate of adolescents, respectively.
Table 13. Parents’ involvement in internet use and their children’s cyberbullying experience rate.
Table 14. Interaction between parents and children and children’s cyberbullying experience rate.
Table 15. Reliability of friend relationships and cyberbullying experience rate.
To analyze the correlation, the following three hypotheses are established:
Hypothesis 4 (H4).
Parents’ internet involvement and cyberbullying experience rates are negatively correlated.
Hypothesis 5 (H5).
Interaction between parents and children and their cyberbullying experience rates are negatively correlated.
Hypothesis 6 (H6).
Reliability of friendship relationships and cyberbullying experience rates are negatively correlated.
The results of the correlation analysis to analyze whether the above three hypotheses are established are shown in Table 16, Table 17 and Table 18, respectively. In Table 16, Table 17 and Table 18, the experience rate includes both the rate of cyberbullying and the rate of cyber victimization.
Table 16. Correlation of parents’ involvement in internet use and their children’s cyberbullying experience rates.
Table 17. Correlation of interaction between parents and children and the children’s cyberbullying experience rates.
Table 18. Correlation of reliability of the friend relationship and cyberbullying experience rate.
Parents’ involvement in internet use shows no statistically significant correlation with the adolescents’ cyberbullying experience (r = −0.896, p > 0.05). Therefore, it can be seen that Hypothesis 4 cannot be adopted.
Interaction between parents and children shows a statistically significant negative correlation with cyberbullying experience rates (r = −0.970, p < 0.05). That is, the higher the interaction with parents, the lower the cyberbullying experience rate. Therefore, it can be seen that Hypothesis 5 is supported.
Reliability of the friend relationship shows a statistically significant negative correlation with the cyberbullying experience rate (r = −0.994, p < 0.01). In other words, the higher the reliability of the friend relationship, the lower the cyberbullying experience rate. Therefore, it can be seen that Hypothesis 6 is supported.

3.6. Analysis of Various Factors of Cyberbullying

In this section, we discuss the reasons for cyberbullying in adolescents in various ways.
According to [3], the reasons for cyberbullying are those shown in Table 19. As shown in Table 19, 45.0% of the respondents said, ‘The other party did it first, to retaliate’ as the reason for cyberbullying behavior in 2019. In addition, the number of adolescents who say that the other party did it first (to retaliate) has increased every year since 2017.
Table 19. Reasons for cyberbullying.
In addition, Table 20 shows the post-abuse psychological state, according to [3]. It can be seen that 51.9 percent of students who committed cyberbullying felt “sorry and regretful,” while 49.0 percent were “worried about having problems”.
Table 20. Post-abuse psychological state of cyberbullying perpetrators.
As Table 19 and Table 20 show, the cyberbullying is impulsive and an immediate retaliation when he or she is victimized. It can also be concluded that once an attack occurs, the cyberbullying perpetrator regrets his or her actions or fears the occurrence of subsequent events.
Meanwhile, let us take a look at the victim’s response and psychological status. First, Table 21 shows the victim’s response, where 36.6 percent of students who experienced cyberbullying experienced “blocking the other person or deleting or changing their own IDs or emails”, while 26.7 percent responded that “the other person was asked to delete the abuse or to apologize directly”.
Table 21. Cyberbullying victim’s response.
Meanwhile, Table 22 shows why the victims did not respond after the cyber victimization. Of the reasons for not doing anything after experiencing cyber victimization, in 2019, 75.0 percent said they thought it was nothing, up from 9.1 percent in 2018.
Table 22. Reasons for not responding after cyber victimization.
Table 23 shows the psychological states after the victimizations. In 2019, after experiencing cyber victimization, 54.0 percent of students said they did not think much about it. In addition, 36.3 percent of them felt “the desire for revenge on the other party”, and 20.9 percent experienced “depression, anxiety, and stress”.
Table 23. Psychological states after victimization.
Furthermore, the following Table 24 shows cyberbullying and cyber victimization experience rates by school and gender [3]. Note that both rates mean both cyberbullying and cyber victimization experience rates.
Table 24. Cyberbullying and cyber victimization experience rates by school and gender.
As Table 24 shows, cyberbullying and victimization experiences among elementary, middle, and high school students decreases in the order of middle school, high school, and elementary school students. Additionally, by gender, male students have a higher experience rate of both cyberbullying and cyber victimization than female students.

4. Discussion

A modern knowledge and information society provides us with many benefits. Among the various benefits we enjoy, online meetings in cyberspace using information and communication technology and smart communication technology are particularly useful for us. In other words, we can exchange or share various opinions through these communication tools. However, this online communication creates not only advantages but also various negative impacts. The most common of these negative impacts is cyberbullying, especially for adolescents whose information and communication ethics are not properly established.
As a result of the analysis of cyberbullying so far, the following results have been obtained. First, the most common type of cyberbullying in adolescents is verbal violence. Second, the most common means of cyberbullying is instant messaging. Third, the most common form of cyberbullying occurs between individuals. Fourth, the interaction between parents and children show a statistically significant negative correlation with cyberbullying experience rates. Fifth, the reliability of friend relationships shows a statistically significant negative correlation with cyberbullying experience rates. Additionally, from Table 21, Table 22 and Table 23, we can see that victims are shown to be passive in their response to victimization. Moreover, the victims were either afraid or too passive to report their own abuse. The victims, meanwhile, can be seen as trying to ignore the fact of the damage to themselves.
The above results imply the following. First, cyberbullying occurs spontaneously among adolescents. The common characteristics of cyberbullying are summarized as verbal violence, instant messaging, and communication between individuals. In other words, their common characteristic is that communication among adolescents can be improvised in real-time. Adolescents can be considerate in an environment where they can afford to think, even a little, but in real-time media space, they have no choice but to improvise. Second, adolescents who are victims of cyberbullying are overly passive about cyberbullying and even ashamed of their own abuse. This can be attributed to the social perception that it is the victim’s fault for providing the cause of cyberbullying to some extent. Third, cyberbullying perpetrators are insensitive to their own cyberbullying behaviors and do not regret their actions. This can be attributed to the fact that there is anonymity, due to the nature of cyberspace, and that they can hide themselves, making them bolder than in the real world. Fourth, improving the interpersonal skills of adolescents, such as improved interaction with parents and improved reliability of friend relationships, can reduce cyberbullying and cyber victimization experiences.
Therefore, in order to solve cyberbullying in adolescents, we propose the following. First, the best way to solve cyberbullying in adolescents is prevention, not healing. What is needed most of all for prevention is to strengthen information and communication ethics education for them. It is necessary to provide after-school programs and various special lectures, as well as public education provided by schools. Second, various means for cyberbullying victims to report their damages justly should be provided. In other words, they should be able to report the abuse quickly through online civil petitions, and they should also know the process of handling their report transparently. Third, adolescents should be encouraged to use non-real-time media such as email and bulletin boards, not real-time media such as instant messaging. In the case of non-real-time media, they can refrain from their actions and also cancel their actions. Fourth, there should be more opportunities to improve interaction with parents at home, and a variety of programs should be offered to increase trust with friends.

5. Conclusions

The purpose of this study is to investigate the causes of cyberbullying among Korean adolescents. The purpose of this study, in particular, is to analyze the types, means, and forms of cyberbullying among adolescents. We were also trying to find the root cause of cyberbullying. For this study, the analysis was made based on the nationwide survey of cyberbullying status reports by the Korea Information Society Agency. In addition, two methods of analysis were performed, parametric and nonparametric, to induce reliable statistical analysis results. The conclusions of both methods of analysis were the same. The results of the analysis based on the data for the last three years are as follows. First, the statistically significant type of cyberbullying in adolescents is verbal violence. Second, a statistically significant means of cyberbullying is instant messaging. Third, the statistically significant form of cyberbullying occurs between individuals. On the other hand, the correlation between the interpersonal relationship of adolescents and the cyberbullying experience rates was analyzed, and the following results were obtained. First, the interaction between parents and children showed a statistically significant negative correlation with cyberbullying experience rates. That is, the higher the interaction with parents, the lower the cyberbullying experience rate. Second, the reliability of friend relationships showed a statistically significant negative correlation with cyberbullying experience rates. That is, the higher the reliability of friend relationships, the lower the cyberbullying experience rate.
The future research works of this study are as follows. First, it is necessary to analyze the causes of cyberbullying and its countermeasures in more depth. In other words, various interviews and in-depth analysis are needed. Second, it is necessary to develop teaching materials that can prevent and cure cyberbullying among adolescents. These teaching materials should be useful in real life by providing various examples as well as theories.

Concluding Remarks

My main research area is information education, and specific research areas include information education for the disabled, gifted education in computer science, and information and communication ethics education. I am especially interested in etiquette in the cyberspace of adolescents in the field of information and communication ethics education, and I am also researching the causes and prevention of cyberbullying in cyberspace. The purpose of this research is to analyze the causes of cyberbullying in Korean adolescents based on national statistical data and present preventive measures.

Funding

This work was supported by the 2020 Research Fund of Seoul National University of Education.

Acknowledgments

The author would like to express my gratitude to Le Gruenwald (School of Computer Science, University of Oklahoma, USA) for showing me an exemplary path as a researcher.

Conflicts of Interest

The author declares no conflict of interest.

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