• Journal of Information Technology Applications and Management
• /
• v.25 no.1
• /
• pp.87-104
• /
• 2018

The internet is spreading widely and malicious comments which is a negative aspect is increasing. Previous studies have considered anonymity as a cyber characteristic of malicious comments. However, there are a theoretical confusion due to inconsistent results. In addition, the dissemination, one of cyber characteristics, have been mentioned the theoretical relationship on malicious comments, but measurement and empirical study about dissemination were still limited. Therefore, this study developed a measurement of dissemination and investigated the relationship between cyber characteristics (anonymity, dissemination) and malicious comments on Facebook. As a result of research, this study identified that anonymity is not significant on malicious comments and discovered that the dissemination of cyber space has a direct influence on malicious comments. This study suggests that information systems can contribute to malicious comments researches by proposing cyber characteristics.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.8 no.12
• /
• pp.817-826
• /
• 2018

As malicious comments are emerging as social problems, the solution is needed. Many studies have been conducted in various perspectives to understand and prevent malicious comments. In the previous researches, the neutralization of malicious comments has attracted attention as an important factor explaining the malicious comments, but the difference of the degree of neutralization according to the gender has not been rarely considered. In addition, although there are many environmental characteristics that are different from reality in online, research with malicious comments is insufficient. Based on these facts, this study examined moderating effects of gender on relationship between malicious comments and neutralization, and demonstrated the effects of online environmental factors (anonymity, lack of social presence) on malicious comments. As a result of the study, we discovered that the influence of online environmental factors was not found, but neutralization of malicious comments had strong direct influence on malicious comments and moderating effect of gender difference. Based on the results of this study, we discuss academic and practical implications and suggest limitations of research and future research directions.

• Smart Media Journal
• /
• v.11 no.2
• /
• pp.18-24
• /
• 2022

Problems caused by malicious comments occur on many social media. In particular, YouTube, which has a strong character as a medium, is getting more and more harmful from malicious comments due to its easy accessibility using mobile devices. In this paper, we designed and implemented a YouTube malicious comment detection system to identify malicious comments in YouTube contents through LSTM-based natural language processing and to visually display the percentage of malicious comments, such commentors' nicknames and their frequency, and we evaluated the performance of the system. By using a dataset of about 50,000 comments, malicious comments could be detected with an accuracy of about 92%. Therefore, it is expected that this system can solve the social problems caused by malicious comments that many YouTubers faced by automatically generating malicious comments statistics.

• The Journal of the Korea Contents Association
• /
• v.21 no.9
• /
• pp.750-761
• /
• 2021

Even though the replying comments on Internet articles have positive effects on discussions and communications, the malicious comments are still the source of problems even driving people to death. Automatic detection of malicious comments is important in this respect. However, the current filtering method of the malicious comments, based on forbidden words, is not so effective, especially for the replying comments written in Korean. This paper proposes a new filtering approach based on morpheme analysis, identifying coarse and polite morphemes. Based on these two groups of morphemes, the soundness of comments can be calculated. Further, this paper proposes various impact measures for comments, based on the soundness. According to the experiments on malicious comments, one of the impact measures is effective for detecting malicious comments. Comparing our method with the clean-bot of a portal site, the recall is enhanced by 37.93% point and F-measure is also enhanced up to 47.66 points. According to this result, it is highly expected that the new filtering method based on morpheme analysis can be a promising alternative to those based on forbidden words.

• Journal of Digital Convergence
• /
• v.16 no.12
• /
• pp.197-206
• /
• 2018

The harmful effects of online malicious comments are continuously increasing. Many previous studies have confirmed that neutralization of malicious comments is a key predictor. Neutralization is theoretically composed of seven multidimensional concepts, and the significance of neutralization factors varies depending on the type of deviant behavior. This study focuses on the fact that the malicious comment researches have considered the neutralization techniques in a single dimension as opposed to demonstrating the multidimensional neutralization techniques in the deviant behavior research. On the other hand, the role of arbitrator in deviant behavior can contribute to restraining deviant behavior, but the research of intervention intention is relatively lacking in malicious comments research. This study, composed of two complementary studies, tried to find out the related factors of malicious comments and intervention intention. As a result of study, This study revealed that malicious commentator uses the neutralization techniques of condemn the condemners and denial of responsibility. In addition, we found that affective empathy has a significant effect on the intervention intention in malicious comments.

• The Journal of the Korea Contents Association
• /
• v.19 no.1
• /
• pp.548-558
• /
• 2019

Along generalization of internet news comments, malicious comments have been spread and made many social problems. Because writings reflect human mental state or trait, analyzing malicious comments, human mental states could be inferred when they write internet news comments. In this study, we analyzed malicious comments of English and Korean speaker using LIWC and KLIWC. As a result, in both English and Korean, malicious comments are commonly more used in sentence, word phrase, morpheme, word phrase per sentence, morpheme per sentence, positive emotion words, and cognitive process words than normal comments, and less used in the third person singular, adjective, anger words, and emotional process words than normal comments. This means people are state that they can not control their feeling such as anger and can not think well when they write news comments. Therefore, when internet comments were written, service provider should consider the way that commenters monitor own writings by themselves and that they prevent the other users from getting close to comments included many negative-emotion words. In other sides, it is discovered that English and Korean malicious comments was discriminated by authenticity. In order to be more objective, gathering data from various point of time is needed.

• Asia pacific journal of information systems
• /
• v.31 no.1
• /
• pp.1-16
• /
• 2021

Cyberbullying has become a social problem as malicious text messages and online comments among teenagers have increased in the late 2000s. Some serious reporting has attempted to impress on us the need to pay more attention to reducing malicious online content as a typical type of cyberbullying. Meanwhile, despite environmental changes that have made it easier to report perpetrators of such messages, it is often the case that the crime occurs in a public place and is tolerated. However, there is a growing tendency for people to exhibit the bystander effect, the problem of personal indifference to witnessing or knowing about crimes, but individuals do not offer any means of help to a victim when other people are present. This effect is rampant in the case of cybercrimes. This study aims to extract the motivations behind posting malicious comments through in-depth interviews and to suggest recommendations for relative issues by demonstrating how the bystander effect can be reduced using causal relationship diagrams of the system dynamics methodology. Hopefully, this work will contribute to a better understanding of factors that could cause a decrease in malicious online comments.

• Knowledge Management Research
• /
• v.17 no.4
• /
• pp.191-213
• /
• 2016

Since the smartphone era has spurred world-over, social network services have become a part of people's daily lives. However, this relatively new phenomenon of technology development raises several negative side effects such as cyberbullying. One of the representative cases of cyberbullying is posting malicious comments online. Multiple social issues arising from this have given impetus to the "benevolent comments campaign" in order to restrain the diffusion of malicious comments. Benevolent comments have advantages that generate positive externalities such as inspiring ethics for an appropriate internet culture, but there is a lack of theoretical research on the deeper understanding of posting benevolent comments. This study thus aims to extract the motivations behind posting benevolent comments through in-depth interviews and suggest alternatives for relative issues through the causal relationship diagram of the system dynamics methodology. This work contributes to our understanding of the factors that affect the increase and decrease in benevolent comments in distinct structural frameworks.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.20 no.2
• /
• pp.260-267
• /
• 2016

The Internet has brought lots of changes to us sharing information mutually. However, as all social symptom have double-sided character, it has serious social problem. Vicious users have been taking advantage of anonymity on the Internet, stating comments aggressively for defamation, personal attacks, privacy violation and more. Malicious comments on the Internet are creating the biggest problem regarding unlawful acts and insults which occur on the Internet. In order to solve the issues, several studies have been done to efficiently manage the comments. However, there are limitations to recognize modified malicious vocabulary in previous research. So, in this paper, we propose a malicious comments detection technique by improving limitation of previous studies. The experimental result has shown accuracy of 87.8% providing higher accuracy as compared to previous studies done.

• Journal of the Korea Convergence Society
• /
• v.11 no.6
• /
• pp.23-28
• /
• 2020

A comment system is essential for communication on the Internet. However, there are also malicious comments such as inappropriate expression of others by exploiting anonymity online. In order to protect users from malicious comments, classification of malicious / normal comments is necessary, and this can be implemented as text classification. Text classification is one of the important topics in natural language processing, and studies using pre-trained models such as BERT and graph structures such as GCN and GAT have been actively conducted. In this study, we implemented a comment classification system using BERT, GCN, and GAT for actual published comments and compared the performance. In this study, the system using the graph-based model showed higher performance than the BERT.