• Journal of Information Science Theory and Practice
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• v.9 no.1
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• pp.24-34
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• 2021

The popularity of social networking sites (SNS) has facilitated communication between users. The usage of SNS helps users in their daily life in various ways such as sharing of opinions, keeping in touch with old friends, making new friends, and getting information. However, some users misuse SNS to belittle or hurt others using profanities, which is typical in cyberbullying incidents. Thus, in this study, we aim to identify profane words from the ASKfm corpus to analyze the profane word distribution across four different roles involved in cyberbullying based on lexicon dictionary. These four roles are: harasser, victim, bystander that assists the bully, and bystander that defends the victim. Evaluation in this study focused on occurrences of the profane word for each role from the corpus. The top 10 common words used in the corpus are also identified and represented in a graph. Results from the analysis show that these four roles used profane words in their conversation with different weightage and distribution, even though the profane words used are mostly similar. The harasser is the first ranked that used profane words in the conversation compared to other roles. The results can be further explored and considered as a potential feature in a cyberbullying detection model using a machine learning approach. Results in this work will contribute to formulate the suitable representation. It is also useful in modeling a cyberbullying detection model based on the identification of profane word distribution across different cyberbullying roles in social networks for future works.

• Journal of the Korea Convergence Society
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• v.10 no.2
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• pp.349-359
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• 2019

The purpose of this study is to explore and deeply understand the essence and meaning of the bullying experiences of school bullies. Data were collected through in-depth dividual interviews and analyzed using Colaizzi phenomenological analysis methodology. Participants of this study were 16 adolescents with compulsory education due to school bullying. Data collection was conducted through in-depth interviews from May to August, 2018. The results of the analysis were derived from 13 theme clusters and 5 categories, focusing on causes of school bullying, factors contributing bullying, and experiences after bullying. Bullying experienced by school bullies were categorized as followed: 'Difficult to empathize with others', 'Uncontrolled anger behavior', 'No hope for the future'. 'Gain from bullying', and 'Difficulty of daily life'. The results of this study are significant in providing basic data to provide practical help and support to school bullies.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.59-66
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• 2023

Text mining (TM) is most widely used to find patterns from various text documents. Cyber-bullying is the term that is used to abuse a person online or offline platform. Nowadays cyber-bullying becomes more dangerous to people who are using social networking sites (SNS). Cyber-bullying is of many types such as text messaging, morphed images, morphed videos, etc. It is a very difficult task to prevent this type of abuse of the person in online SNS. Finding accurate text mining patterns gives better results in detecting cyber-bullying on any platform. Cyber-bullying is developed with the online SNS to send defamatory statements or orally bully other persons or by using the online platform to abuse in front of SNS users. Deep Learning (DL) is one of the significant domains which are used to extract and learn the quality features dynamically from the low-level text inclusions. In this scenario, Convolutional neural networks (CNN) are used for training the text data, images, and videos. CNN is a very powerful approach to training on these types of data and achieved better text classification. In this paper, an Ensemble model is introduced with the integration of Term Frequency (TF)-Inverse document frequency (IDF) and Deep Neural Network (DNN) with advanced feature-extracting techniques to classify the bullying text, images, and videos. The proposed approach also focused on reducing the training time and memory usage which helps the classification improvement.

• Korean Journal of Culture and Social Issue
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• v.9 no.1
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• pp.81-114
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• 2003

This study examines the basis and change of delinquent behavior among Korean adolescents. Theoretical framework was developed and qualitative analysis of delinquency behavior was examined. In order to understand the basis and change of juvenile delinquency, the influence of family environment, school environment and individual factors were investigated through cross-sectional and longitudinal studies. The results of the findings can be summarized into the following six main points: 1) two subcultures of adolescent functioning could be ascertained, 2) the decrease in social support and increase in moral disengagement were directly related to a rise in juvenile delinquency, 3) family disintegration contributed to juvenile delinquency, 4) peer influence help to raise juvenile delinquency, 5) schools were unable to give hope to those students who were not doing well in school and were ineffective in dealing with juvenile delinquents, and 6) the phenomenon of juvenile delinquency points to the importance of opening up the closed school system and closed society, allowing individual diversity and skills to be recognized.

• Journal of Preventive Medicine and Public Health
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• v.36 no.4
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• pp.373-376
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• 2003

Objectives : Peripheral blood-buffy coat fractions (N=14,956) have been stored at $-70^{\circ}C$ in the headquarter of the Korean Multicenter Cancer Cohort (KMCC), since 1993. To study the future molecular etiology of cancers using specimens of the cohort, properly stored specimens are necessary, Therefore, the DNA-viability of the bully coat samples was investigated. Methods : Buffy coat fraction samples were randomly selected from various collection areas and years (N=100). The DNA viability was evaluate from the UV-absorbent ratios at 260/280nm and the PCH for $\beta$-globin was performed with genomic DNA isolated from the buffy coat. Results : PCR products were obtained from 85 and 98% of the C and H area-samples, respectively, using 50 or $100{\mu}l$ of the buffy coat. There were significant differences in the yields of the PCR-amplifications from the C and H areas (p<0.05), which was due to differences in the homogenization of the buffy coat fractions available as aliquots. The PCR-products were obtained from all of the samples (N=7) stored at the C area-local confer, but the other aliquots stored at the headquarter were not PCR-amplified, Therefore, the PCR products in almost all the samples, even including the DNA-degraded samples, were obtained. In addition, an improvement in the DNA isolation, i,e. approx. 1.6 fold, was found after using extra RBC lysis buffer. Conclusions : PCR products for $\beta$-globin were obtained from nearly all of the samples. The regional differences in the PCR amplifications were thought to have originated from the different sample-preparation and homogenization performance. Therefore, the long term-stored buffy coat species at the KMCC can be used for future molecular studies.