• Title/Summary/Keyword: fake design

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A Study of Fake Design in the Fashion of the 2000s (2000년대 패션에 표현된 페이크 디자인 연구)

  • Park, Eun-Kyung
    • Journal of the Korean Society of Costume
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    • v.60 no.3
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    • pp.110-122
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    • 2010
  • The purpose of this study is to analyze the expressional traits and internal meanings of fake design in the 2000s' fashion, based on study of art and design area. For achieving the purpose, this study performed related research works and a demonstrative analysis of fashion collection photographs. The scope of this study is from 2000 to 2009. The results are as follows. Fake design uses trompe-l'oeil which is an art technique related to the meanings of 'deceive or fool the eye'. This eye-deceiving technique has been used for a long time in the art, and particularly noticed as one of techniques of Surrealism. Art works using trompe-l'oeil express familiar and unreasonable world at the same time, and also the fusion of reality and fabrication. Fake design in design area of the 2000s makes people take daily life in unfamiliar way by unusualness and breaking the boundary between real and fake. By fake design, people can enjoy fun and a sense of freedom with amusement rather than unpleasant of being deceived. Fake design in the fashion of the 2000s uses eye-deceiving technique and also focuses on the concept of 'fake'. The expressional traits were categorized as realistic expression, surrealistic expression and fake value expression. The internal meanings were analyzed as breaking boundary between real and fake, rediscover dailiness, new attitude to traditional thinking. In conclusion, fake design in the fashion of the 2000s gives playfulness, fun, feeling of release and will be pursued continually.

A Study on Visual Humor Expression in Fake Technique Fashion

  • Kim, Jinyoung;Kan, Hosup
    • Journal of Fashion Business
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    • v.21 no.3
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    • pp.43-57
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    • 2017
  • This study concerns visual humor in fake technique fashion. While previous studies focused mainly on expression techniques of fake technique fashion, this study analyzed visual humor in fake technique fashion based on classification criteria of visual humor expression techniques, differenting this study from other studies. The purpose of this study was to derive visual humor in fake technique fashion by classifying cases of fake technique fashion, and re-classifying outcomes of primary classification based on criteria of visual humor expression techniques. As for methods, this theoretical study was conducted on humor, expression techniques of visual humor, fake fashion and fake expression techniques through literature review. Subsequently, 485 fake technique fashion images obtained from research were classified by expression techniques, and cases of fake technique fashion were analyzed. In addition, by combining this theoretical study with case studies, fake technique fashion was re-classified according to criteria of visual humor expression techniques to derive the characteristics of visual humor in fake technique fashion. Based on visual humor expression techniques, visual humor in fake technique fashion was created by distortion and transformation that made the fake look real by distorting or transforming the fake, enlargement and reduction that created new forms by altering familiar forms, and typeplay that added fun by changing familiar luxury logos into various forms.

Algorithm Design to Judge Fake News based on Bigdata and Artificial Intelligence

  • Kang, Jangmook;Lee, Sangwon
    • International Journal of Internet, Broadcasting and Communication
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    • v.11 no.2
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    • pp.50-58
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    • 2019
  • The clear and specific objective of this study is to design a false news discriminator algorithm for news articles transmitted on a text-based basis and an architecture that builds it into a system (H/W configuration with Hadoop-based in-memory technology, Deep Learning S/W design for bigdata and SNS linkage). Based on learning data on actual news, the government will submit advanced "fake news" test data as a result and complete theoretical research based on it. The need for research proposed by this study is social cost paid by rumors (including malicious comments) and rumors (written false news) due to the flood of fake news, false reports, rumors and stabbings, among other social challenges. In addition, fake news can distort normal communication channels, undermine human mutual trust, and reduce social capital at the same time. The final purpose of the study is to upgrade the study to a topic that is difficult to distinguish between false and exaggerated, fake and hypocrisy, sincere and false, fraud and error, truth and false.

Identification Systems of Fake News Contents on Artificial Intelligence & Bigdata

  • KANG, Jangmook;LEE, Sangwon
    • International journal of advanced smart convergence
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    • v.10 no.3
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    • pp.122-130
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    • 2021
  • This study is about an Artificial Intelligence-based fake news identification system and its methods to determine the authenticity of content distributed over the Internet. Among the news we encounter is news that an individual or organization intentionally writes something that is not true to achieve a particular purpose, so-called fake news. In this study, we intend to design a system that uses Artificial Intelligence techniques to identify fake content that exists within the news. The proposed identification model will propose a method of extracting multiple unit factors from the target content. Through this, attempts will be made to classify unit factors into different types. In addition, the design of the preprocessing process will be carried out to parse only the necessary information by analyzing the unit factor. Based on these results, we will design the part where the unit fact is analyzed using the deep learning prediction model as a predetermined unit. The model will also include a design for a database that determines the degree of fake news in the target content and stores the information in the identified unit factor through the analyzed unit factor.

News Article Identification Methods with Fact-Checking Guideline on Artificial Intelligence & Bigdata

  • Kang, Jangmook;Lee, Sangwon
    • International Journal of Advanced Culture Technology
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    • v.9 no.3
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    • pp.352-359
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    • 2021
  • The purpose of this study is to design and build fake news discrimination systems and methods using fact-checking guidelines. In other words, the main content of this study is the system for identifying fake news using Artificial Intelligence -based Fact-checking guidelines. Specifically planned guidelines are needed to determine fake news that is prevalent these days, and the purpose of these guidelines is fact-checking. Identifying fake news immediately after seeing a huge amount of news is inefficient in handling and ineffective in handling. For this reason, we would like to design a fake news identification system using the fact-checking guidelines to create guidelines based on pattern analysis against fake news and real news data. The model will monitor the fact-checking guideline model modeled to determine the Fact-checking target within the news article and news articles shared on social networking service sites. Through this, the model is reflected in the fact-checking guideline model by analyzing news monitoring devices that select suspicious news articles based on their user responses. The core of this research model is a fake news identification device that determines the authenticity of this suspected news article. So, we propose news article identification methods with fact-checking guideline on Artificial Intelligence & Bigdata. This study will help news subscribers determine news that is unclear in its authenticity.

Development of a Deep Learning Model for Detecting Fake Reviews Using Author Linguistic Features (작성자 언어적 특성 기반 가짜 리뷰 탐지 딥러닝 모델 개발)

  • Shin, Dong Hoon;Shin, Woo Sik;Kim, Hee Woong
    • The Journal of Information Systems
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    • v.31 no.4
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    • pp.01-23
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    • 2022
  • Purpose This study aims to propose a deep learning-based fake review detection model by combining authors' linguistic features and semantic information of reviews. Design/methodology/approach This study used 358,071 review data of Yelp to develop fake review detection model. We employed linguistic inquiry and word count (LIWC) to extract 24 linguistic features of authors. Then we used deep learning architectures such as multilayer perceptron(MLP), long short-term memory(LSTM) and transformer to learn linguistic features and semantic features for fake review detection. Findings The results of our study show that detection models using both linguistic and semantic features outperformed other models using single type of features. In addition, this study confirmed that differences in linguistic features between fake reviewer and authentic reviewer are significant. That is, we found that linguistic features complement semantic information of reviews and further enhance predictive power of fake detection model.

Controversy and Guideline Suggestion Surrounding Fake News in the Digital Media Age (가짜뉴스(Fake News) 현황분석을 통해 본 디지털매체 시대의 쟁점과 뉴스콘텐츠 제작 가이드라인)

  • Kwon, Mahnwoo;Jun, Yong Woo;Im, Hajin
    • Journal of Korea Multimedia Society
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    • v.18 no.11
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    • pp.1419-1426
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    • 2015
  • Distinguishing border between news and advertising is disappearing. Traditional journalism considered editorial part deals news and ad part handle commercial messages. But now this classification is meaningless. Current news consumers do not separate advertising content and non-advertising content. In Korea, making fake news or paid news pages is becoming social problem. Fake news uses various camouflages to pretend to be real news. This paper descriptively analyzed Korean fake news cases and suggested some guidelines for publishing news. We analyzed 3 major newspaper web sites from July to September, 2014. These three newspapers publish section pages everyday containing fake news or sponsored news. Totally more than one thousand articles were selected for content analysis. We coded the numbers of fake news, day of the week, the rate of sponsored news, average fake news publication number per pages, the conformity between news and advertising, and the type of fake news. We also coded the number of sponsored news article in day sections. We used method of comparing the advertising contents and news articles. As a result, 24.8% of news article were published for the advertising sponsors. Advertorial or fake news were sometimes arranged same pages the same day. We coded the conformity between same advertising and news content. More than 60 percent (60.9%) of fake news match with their sponsors. PR style of fake news is top and advertising type of fake news is the lowest.

A Study on Modern Fake Fashion Based on Simulacre Concept of Baudrillard (보드리야르의 시뮬라크르 개념을 통한 현대 페이크 패션 연구)

  • Kim, Koh Woon;Chun, Jae Hoon
    • Journal of the Korean Society of Clothing and Textiles
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    • v.40 no.4
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    • pp.600-614
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    • 2016
  • This study specifies the definition and characteristics of fake fashion by categorizing cases through an analytical framework that uses the concept of simulacre, which is one of the theories that explains the reproduction of images and symbols in a modern consumer society. The presentation stages of modern fake fashion based on Baudrillard's concept of simulacre are as follows: Stage 1 focuses on the realistic imitation of the original, Stage 2 maintains a similarity with the original while transforming through the distortion of shape or visual perception, Stage 3 is the reality of the original which has become significantly vague and actively involves the designer's creativity, and Stage 4 forms a new value and an independent aura beyond reproducing the original. The presentation techniques of modern fake fashion viewed in the concept of simulacre can be classified into optical illusions by reproduction, use of a fake object, use of unusual shapes, and re-signifying through borrowing. As a result of applying the collected cases to the analytical framework, image reproduction in Stage 1 with imitative nature is a counterfeit that cannot be regarded as fake fashion, and fake fashion in Stage 4 (that can be referred to as simulacre) is fashion with symbolic and multiple meanings with new and creative designs. Modern fake fashion analyzed in the concept of simulacre transforms or reproduces the preexisting original with the purpose of merely creating original designs as well as acts as a new symbolic signal that creates a new aura and sets a trend with a message.

A Study on the Environment-Friendly Design Expressed in Fashion -Focused on the Korean Designer′s Work since 1990- (패션에 표현된 환경친화적 디자인의 특성 -1990년대 이후의 국내 디자이너 작품을 중심으로-)

  • 김문숙;최나영
    • The Research Journal of the Costume Culture
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    • v.6 no.2
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    • pp.163-180
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    • 1998
  • The purpose of this study is to investigate the main characteristics of the environment-friendly design expressed in Koran fashion. Environment-friendly design can be categorized into choice of material, extension of products life cycle, and recycling design. In this study, Korean fashion designers can be found having the conciousness of environment for fashion design since 1990. First, in choice of material, the designers used Natural fibers which are cotton, linen, wool, and etc, and used natural dyes. Some of the designers have moved from using real fur to using fake fur for animal welfare. But fake furs produced from synthetic or regenerated fibers have the environmental problems during textile production processes. Some of the designers used fake leather made from the skins of an edible fish which are otherwise going to waste. Secondly, Design for extension of products life cycle can economize the resources and energy. Design for extension of products life cycle are classified into reversible clothing, many function clothing, modular style, patina clothing, simple style, and layered look. Finally, recycling design are classified into recycling of daily necessaries and expression techniques of recycling design which are designer's works used patchwork, mash techniques, and handmade of knits or buttonhole stitch.

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A Study on the Design of a Fake News Management Platform Based on Citizen Science (시민과학 기반 가짜뉴스 관리 플랫폼 연구)

  • KIM, Ji Yeon;SHIM, Jae Chul;KIM, Gyu Tae;KIM, Yoo Hyang
    • Journal of Science and Technology Studies
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    • v.20 no.1
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    • pp.39-85
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    • 2020
  • With the development of information technology, fake news is becoming a serious social problem. Individual measures to manage the problem, such as fact-checking by the media, legal regulation, or technical solutions, have not been successful. The flood of fake news has undermined not only trust in the media but also the general credibility of social institutions, and is even threatening the foundations of democracy. This is why one cannot leave fake news unchecked, though it is certainly a difficult task to accomplish. The problem of fake news is not about simply judging its veracity, as no news is completely fake or unquestionably real and there is much uncertainty. Therefore, managing fake news does not mean removing them completely. Nor can the problem be left to individuals' capacity for rational judgment. Recurring fake news can easily disrupt individual decision making, which raises the need for socio-technical measures and multidisciplinary collaboration. In this study, we introduce a new public online platform for fake news management, which incorporates a multidimensional and multidisciplinary approach based on citizen science. Our proposed platform will fundamentally redesign the existing process for collecting and analyzing fake news and engaging with user reactions. People in various fields would be able to participate in and contribute to this platform by mobilizing their own expertise and capability.