• Cross-Cultural Studies
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• v.35
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• pp.237-268
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• 2014

Examining swear words found in Korean and English, we aim to answer the following two questions: (i) 'What words develop into swear words?' and (ii) 'Why they do?' The utility of a swear word is frequently recognized as intimidation directed towards an opponent, emotional catharsis, and solidarity building among in-group members (Jay 1992, 2000, Kim 1997). We seek to go beyond this simple enumeration of possible functions of swearing and suggest an underlying mechanism at work to explain how these functions are achieved and why only certain types of words are employed in this pursuit. A close examination reveals that a swear word must contain either taboo or sadism as an essential component. Sexual pleasure adds another dimension to the basic components. Thus, if an expression contains a subset of the component set {taboo, sadism, sex} in its semantics, it becomes available for swearing (one of the underlined components must be included in the set). For example, many religiously sacred expressions and words for excretion are common swear words as they violate social and religious taboo. On the other hand, words referring to social minorities are a convenient target for sadism. Furthermore, words describing sexual activity contain all three components, violating social taboo, evoking sadism, and giving the initiator guilty sexual pleasure. A combination of the components can produce an emotional effect called catharsis for the initiator. When directed towards others, these components, especially taboo and sadism, can be exploited as a verbal attack, an intimidation, preceding or replacing a physical attack. However, solidarity building is analyzed as a secondary function of swearing, achieved by sharing a sense of accomplice when in-group members behave badly together, such as violating social taboo and committing sadism.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.9
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• pp.381-388
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• 2014

In this paper, we deal with implementation issues of an unknown word classifier for middle-school level English writing test. We define the type of unknown words occurred in English text and discuss the detection process for unknown words. Also, we define the type of swear words occurred in students's English writings, and suggest how to handle this type of words. We implement an unknown word classifier with a swear detection module for developing an automatic English writing scoring system. By experiments with actual test data, we evaluate the accuracy of the unknown word classifier as well as the swear detection module.

• The Journal of the Convergence on Culture Technology
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• v.4 no.2
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• pp.107-114
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• 2018

The study is to find out the influence of mother's and father's conflict resolution styles(aggressive and compromising) on adolescents' use of swear words. This study also investigates whether aggression has a mediated effect in terms of the relationship between mother's and father's conflict resolution styles and their children's use of swear words. To this end, self-report type of questionnaire was conducted to 570 students who attend at 6 different middle schools located in Gyeongnam Province. To the exclusion of incomplete and insincere answers, 477 were selected as the raw data of the research. The summarization of the results is as follows: First, the aggressive type of conflict resolution style with mothers has positive correlation with the students' use of swear words. When the conflict resolution style with mothers gets aggressive, their children's use of swear word increases accordingly. Second, it is confirmed that aggression has a mediated effect when it comes to teenagers' use of swear words triggered by mother's aggressive conflict resolution styles and father's aggressive conflict resolution styles. Therefore, if the conflict between children and parents is not appropriately resolved, the children's aggression accumulates and thereby children's use of swear words increases.

• Journal of the Semiconductor & Display Technology
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• v.20 no.1
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• pp.83-87
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• 2021

By the increase of internet usage, communicating online became an everyday thing. Thereby various people have experienced profanity by anonymous users. Nowadays lots of studies tried to solve this problem using artificial intelligence, but most of the solutions were for non-real time situations. In this paper, we propose a Telegram plugin that detects swear words using word2vec, and an algorithm to find the target of the sentence. We vectorized the input sentence to find connections with other similar words, then inputted the value to the pre-trained CNN (Convolutional Neural Network) model to detect any swears. For target recognition we proposed a sequential algorithm based on KoNLPY.

• International Journal of Costume and Fashion
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• v.9 no.2
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• pp.49-66
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• 2009

In the 21st century, the lining design has been interpreted from diverse perspectives, as one of important elements in fashion design. The purpose of this study is to build up the foundation of elementary resources for Korean styled lining design. For this, it was understood through the theoretical research with respect to the history of lining. In order to preparing the standards to develop the lining design in a Korean image, the photos of women' swear collection taken from 2005 SIS to 2009 F/W and the results of marketing research on the women'swear industry were used for the analysis which are studied in three categories: brand symbolism, cultural identity and vogue. Based on these, the design was carried out.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.2
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• pp.25-34
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• 2022

With the development of online services, the ripple effect of negative comments is increasing, and the damage of cyber violence is rising. Various methods such as filtering based on forbidden words and reporting systems prevent this, but it is challenging to eradicate negative comments. Therefore, this study aimed to increase the accuracy of the classification of negative comments using deep learning and blur the parts corresponding to profanity. Two different conditional training helped decide the number of deep learning layers and filters. The accuracy of 88% confirmed with 90% of the dataset for training and 10% for tests. In addition, Grad-CAM enabled us to find and blur the location of swear words in negative comments. Although the accuracy of classifying comments based on simple forbidden words was 56%, it was found that blurring negative comments through the deep learning model was more effective.

• Korean Journal of Childcare and Education
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• v.12 no.2
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• pp.1-17
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• 2016

The purpose of this study was to investigate the difference in elementary school children's human rights sensitivity and the perception of human rights depending on child variables, family variables, school variables, and predictive influences among these variables. The participants were 1,364 elementary school children in the 'Current Status of Korean Children's and Youth's Rights(2013)'. The results of this study were as follows: First, the variables influencing children's human rights sensitivity were school life experience, grade, the degree to which adolescents think they are respected in deciding family issues, gender, experiences of teacher's swear words, experiences of being neglected, and experiences of being bullied at school. Second, the variables influencing children's perception of human rights were gender, experiences of parents' swear words, school life experience, the degree to which adolescents think they are respected in deciding family issues, and father's educational achievements. The results of this study offered fundamental data about the important issues in researching children's rights and the policy implications for enhancing them.

• The Journal of the Korea Contents Association
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• v.9 no.12
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• pp.113-120
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• 2009

Currently the verbal abuse in text message over on-line game is so serious. However we do not have any effective policy or technical tools yet. Till now in order to cope with this problem, the online game service providers have accumulated a set of forbidden words and applied this list on the textual word used in on-line game, which is called 'Swear filter'. But young on-line game players easily avoid this filtering method by coining another words which is not kept in the list. Especially Korean is very easy to make new variations of a vulgar word. In this paper, we propose one smart filtering algorithm to identify newly coined profanities. Important features of our method include the canonical form transformation of coined profanities, semi-global alignment between in the level of consonant and vowel units. For experiment, we have collected more than 1000 newly coined vulgar words in on-line gaming sites and tested these word against our methods. where our system have successfully filtered more than 90% of those newly coined vulgar words.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.141-143
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• 2017

스마트 기기의 발전이 급격히 증가됨에 따라 현대인의 생활은 매우 편리해졌다. 그 반면 스마트 기기로 인한 피해 역시 늘어나고 있다. 청소년의 경우 스마트 폰 과다 사용, 게임 중독뿐만 아니라 SNS를 통한 비속어 문자에 노출되어 정신적으로 괴롭힘을 당하는 일이 많아지고 있다. 본 논문에서는 스마트 폰에 전송된 문자 중 모욕적인 단어나 수치심을 유발하는 단어, 자존감을 떨어지게 하는 단어, 폭력적인 단어가 포함되어 있을 때 부모님이나 학교 담임, 학교폭력담당경찰관에게 자동으로 전달되는 앱을 설계하고자 한다. 폭력 문자가 수신되었을 때 경위를 파악할 수 있고, 상담을 통한 피해 청소년의 괴로움 및 자살충동 등을 미연에 방지할 수 있게 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.414-417
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• 2011

단어 필터링 기법의 개발에 있어서 가장 큰 난제는 정상단어를 금지어로 인식하여 이를 차단하는 오탐지 문제이다. 이를 방지하기 위하여 다양한 문장에 대한 면밀하고 광범위한 검사가 필수적이나 일반적으로 쉽게 접근할 수 있는 데이터는 주로 단어 위주로 구성된 검증 데이터로 문장 또는 구절로 구성된 데이터의 양은 실제 검증에 활용하기에는 충분하지 못하다. 본 논문에서는 웹에서 수집한 방대한 양의 말뭉치 데이터에 반전역정열(Semi-Global Alignment)을 적용하여 주어진 금지어가 사용되거나 금지어와 유사한 단어가 존재하는 구간을 탐색함으로써 단어 필터링 시스템에서 범용적으로 사용될 수 있는 문장형 평가 데이터를 수집하는 시스템을 제안하고 해당 기법을 통하여 수집한 문장 단위 데이터를 분석하고 단어 필터링 시스템이 오탐지 방지를 위해 가져야할 요소들에 대하여 검토해 본다.