• The Journal of the Korea Contents Association
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• v.20 no.2
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• pp.499-510
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• 2020

This study aims to analyze the causes of Internet hate speech, which has recently been emerging as a serious social problem and to seek for countermeasures. The experiences of hate speech are examined through the analysis of college students' essays and the causes and solutions of hate speech are suggested through the in-depth interviews with the experts. College students experience hate speech on the Internet on the basis of attributes such as age, gender, sexual orientation, and regionalism. Online comments on news, social media and online games are the main sources in spreading hate speech. On a personal level the lack of awareness of human dignity and the absence of media education are diagnosed as the reasons for online hate speech. The social reasons for online hate speech lie in the lack of human rights education and the problems of the media. In order to improve the problems of Internet hate speech, various suggestions are proposed on the legal, social and educational levels.

• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.112-119
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• 2023

Traditionally used for networking computers and communications, the Internet has been evolving from the beginning. Internet is the backbone for many things on the web including social media. The concept of social networking which started in the early 1990s has also been growing with the internet. Social Networking Sites (SNSs) sprung and stayed back to an important element of internet usage mainly due to the services or provisions they allow on the web. Twitter and Facebook have become the primary means by which most individuals keep in touch with others and carry on substantive conversations. These sites allow the posting of photos, videos and support audio and video storage on the sites which can be shared amongst users. Although an attractive option, these provisions have also culminated in issues for these sites like posting offensive material. Though not always, users of SNSs have their share in promoting hate by their words or speeches which is difficult to be curtailed after being uploaded in the media. Hence, this article outlines a process for extracting user reviews from the Twitter corpus in order to identify instances of hate speech. Through the use of MPCA (Modified Principal Component Analysis) and ECNN, we are able to identify instances of hate speech in the text (Enhanced Convolutional Neural Network). With the use of NLP, a fully autonomous system for assessing syntax and meaning can be established (NLP). There is a strong emphasis on pre-processing, feature extraction, and classification. Cleansing the text by removing extra spaces, punctuation, and stop words is what normalization is all about. In the process of extracting features, these features that have already been processed are used. During the feature extraction process, the MPCA algorithm is used. It takes a set of related features and pulls out the ones that tell us the most about the dataset we give itThe proposed categorization method is then put forth as a means of detecting instances of hate speech or abusive language. It is argued that ECNN is superior to other methods for identifying hateful content online. It can take in massive amounts of data and quickly return accurate results, especially for larger datasets. As a result, the proposed MPCA+ECNN algorithm improves not only the F-measure values, but also the accuracy, precision, and recall.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1595-1603
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• 2020

Online defamation incidents such as Internet news comments on portal sites, SNS, and community sites are increasing in recent years. Bias and hate expressions threaten online service users in various forms, such as invasion of privacy and personal attacks, and defamation issues. In the past few years, academia and industry have been approaching in various ways to solve this problem The purpose of this study is to build a dataset and experiment with deep learning classification modeling for detecting various bias expressions as well as hate expressions. The dataset was annotated 7 labels that 10 personnel cross-checked. In this study, each of the 7 classes in a dataset of about 137,111 Korean internet news comments is binary classified and analyzed through deep learning techniques. The Proposed technique used in this study is multi-channel CNN model with attention. As a result of the experiment, the weighted average f1 score was 70.32% of performance.

• Informatization Policy
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• v.30 no.2
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• pp.3-21
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• 2023

The recent Internet environment demands a new approach to Internet content regulation. The need for regulation on the Internet has been recognized due to the rise of digital sex crimes, illegal information such as drugs and suicide, fake news, hate speech, false consumer reviews, and harmful content for young people. This article attempts to analyze the legislative, judicial, and administrative aspects of Internet content regulation in Korea. It covers the current status and characteristics of the Internet content regulation law, the judicial judgment on KCSC's communications deliberation and regulation, and the process and characteristics of KCSC's communications deliberation. Problems in Korea's communications deliberation system were addressed through legislative, judicial, and administrative approaches. This article concludes with policy suggestions for improving Internet content regulation in Korea.

• The Journal of the Acoustical Society of Korea
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• v.21 no.4
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• pp.349-360
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• 2002

In ITU H.323 teleconference system, the RTP/RTCP protocol is offered to transfer real-time multimedia stream. Both sender and receiver hate experience in packet loss and jitter which result from network congestion over Internet. Audio quality over Internet depends on the number of lost packets and on jitter between successive packets. The goal of our study is to improve the speech quality over Internet by checking the packet loss characteristics of the network and adopting the but for control management mechanism at the receiver. We suggest a dynamic redundant audio transmission mechanism which examines the packet loss rate and uses the feedback information through RTCP.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.320-326
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• 2022

The use of the Internet has become commonplace for billions of people on the planet. The rapid development of technology, in particular, mobile gadgets, has provided access to communication anywhere, anytime. At the same time, there are growing concerns about the behavior of people on the Internet, in particular, towards each other and social groups in general. This raises the issue of human rights in today's information society. In this study, we focused on human rights such as the right to privacy, confidentiality, freedom of expression, the right to be forgotten, etc. We point to some differences in this regard, in particular between the EU, etc. In addition, we describe the latest legal regulation in this aspect in European countries. Such methods as systemic, factual, formal and legal, to show the factors of formation and development of human rights in the context of digitalization were used. The authors indicate which of them deserve the most attention due to their prevalence and relevance. Thus, we concluded that the technological development of social communications has laid the groundwork for a legal settlement of privacy and opinion issues on the Internet. Simultaneously, jurisdictions address issues on every aspect of human rights on the Internet, based on previous norms, case law, and principles of law. It is concluded that human rights legislation on the Internet will continue to be actively developed to ensure a balance of private and public interests, safe online access and unimpeded access to it.

• International journal of advanced smart convergence
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• v.12 no.1
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• pp.82-91
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• 2023

In 2020 when the COVID-19 pandemic began in full-scale, the WHO Director-General warned of the dangers of an infodemic. The infodemic is a phenomenon in which false information spreads rapidly like an epidemic and causes chaos, and it was noted that the COVID-19 pandemic is not just limited to health problems, but also linked to a variety of issues such as human rights, economic inequality, various discrimination, hate speech, fake news, global governance etc. In the field of education, it is necessary to think about how to connect this global situation with school classes. Accordingly, this study suggested the direction for global citizenship education by analyzing how the infodemic spreads on Korean social media with the case of the recent global COVID-19 pandemic. According to the research results, the rate of negative emotions was higher than positive ones in the emotions that generate infodemic, while anxiety and anger were focused among negative emotions. In addition, the infodemic tended to spread widely with the feelings of anger rather than anxiety, and the feelings of anger led to advocating aggressive policies against certain country and regions. Therefore, global citizenship education is required to focus on a sense of duty and responsibility as a citizen, not on the level of national identity based on an exclusive sense of belonging. Furthermore, global citizenship education needs to lead to presenting a blueprint for education in a way that can enhance the awareness of the global community for joint response to global challenges and realize common prosperity based on sustainability and justice.

• Smart Media Journal
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• v.10 no.4
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• pp.71-79
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• 2021

One of the social aspects that changes as the use of the Internet becomes widespread is communication in online space. In the past, only one-on-one conversations were possible remotely, except when they were physically in the same space, but nowadays, technology has been developed to enable communication with a large number of people remotely through bulletin boards, communities, and social network services. Due to the development of such information and communication networks, life becomes more convenient, and at the same time, the damage caused by rapid information exchange is also constantly increasing. Recently, cyber crimes such as sending sexual messages or personal attacks to certain people with recognition on the Internet, such as not only entertainers but also influencers, have occurred, and some of those exposed to these cybercrime have committed suicide. In this paper, in order to reduce the damage caused by malicious comments, research a method for improving the performance of discriminate malicious comments through feature extraction based on parts-of-speech.

• Journal of the Korea Convergence Society
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• v.12 no.12
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• pp.93-106
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• 2021

Blenderbot 2.0 is a dialogue model representing open domain chatbots by reflecting real-time information and remembering user information for a long time through an internet search module and multi-session. Nevertheless, the model still has many improvements. Therefore, this paper analyzes the limitations and errors of BlenderBot 2.0 from three perspectives: model, data, and dialogue. From the data point of view, we point out errors that the guidelines provided to workers during the crowdsourcing process were not clear, and the process of refining hate speech in the collected data and verifying the accuracy of internet-based information was lacking. Finally, from the viewpoint of dialogue, nine types of problems found during conversation and their causes are thoroughly analyzed. Furthermore, practical improvement methods are proposed for each point of view, and we discuss several potential future research directions.