• Journal of Fashion Business
• /
• v.21 no.3
• /
• pp.43-57
• /
• 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.

• Journal of Information Technology Services
• /
• v.18 no.1
• /
• pp.219-234
• /
• 2019

Fake news threaten democratic elections and causes social conflicts, resulting in major damage. However, the concept of fake news is hard to define, as there is a saying, "News is not fake, fake is not news." Fake news, however, has irreversible characteristics that can not be recovered or reversed completely through post-punishment of economic and political benefits. It is also rapidly spreading in the early days. Therefore, it is very important to preemptively detect these types of articles and prevent their blind proliferation. The existing countermeasures are focused on reporting fake news, raising the level of punishment, and the media & academia to determine the authenticity of the news. Researchers are also trying to determine the authenticity by analyzing its contents. Apart from the contents of fake news, determining the behavioral characteristics of the promoters and its qualities can help identify the possibility of having fake news in advance. The online community has a fake news interception and response tradition through its long-standing community-based activities. As a result, I attempted to model the fake news by analyzing the affirmation-denial analysis and posting behavior by securing the web board crawl of the 'M community' bulletin board during the 2017 Korean presidential election period. Random forest algorithm deemed significant. The results of this research will help counteract fake news and focus on preemptive blocking through behavioral analysis rather than post-judgment after semantic analysis.

• Asian Journal for Public Opinion Research
• /
• v.9 no.1
• /
• pp.25-47
• /
• 2021

This study analyzes 419 fake news items published in India, a fake-news-prone country, to identify the major themes, content types, and sources of social media fake news. The results show that fake news shared on social media has six major themes: health, religion, politics, crime, entertainment, and miscellaneous; eight types of content: text, photo, audio, and video, text & photo, text & video, photo & video, and text & photo & video; and two main sources: online sources and the mainstream media. Health-related fake news is more common only during a health crisis, whereas fake news related to religion and politics seems more prevalent, emerging from online media. Text & photo and text & video have three-fourths of the total share of fake news, and most of them are from online media: online media is the main source of fake news on social media as well. On the other hand, mainstream media mostly produces political fake news. This study, presenting some novel findings that may help researchers to understand and policymakers to control fake news on social media, invites more academic investigations of religious and political fake news in India. Two important limitations of this study are related to the data source and data collection period, which may have an impact on the results.

• Journal of the Korean Society of Costume
• /
• v.60 no.3
• /
• pp.110-122
• /
• 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.

• International Journal of Knowledge Content Development & Technology
• /
• v.11 no.4
• /
• pp.35-51
• /
• 2021

This study measured the effects of fake news and propaganda on managing information on COVID-19 among the Nigerian citizenry. This study examined sources of information on COVID-19 available to the people, evaluated reasons behind spreading fake news, examined how fake news has affected the spread of COVID-19 pandemic in Nigeria, established the consequences of fake news on managing COVID-19 pandemic and as well identified ways to contain fake news at a time like this in Nigeria.It is a survey with a sample size of 375 participants selected using simple random technique. Instrument of data gathering was questionnaire widely distributed in the six geo-political zones of Nigeria using Survey monkey. Data was analysed using frequencies, counts and percentages, tables and charts. Findings revealed that people rely more on radio, television, and social media for information on COVID-19. Fake news is spread by people mostly for political reasons and intention to cause panic. In Nigeria, fake news has led to disbelief of the existence of the virus thereby leading to violation of precautionary measures among the citizenry and lack of trust in the government. Concerted effort on the part of the government is required to give public enlightenment on the danger of fake news. Also, directorate of anti-fake news should be established to censor and reprimand sources of fake news. People should always check source of information to confirm its credibility and be weary of sharing unconfirmed information especially on the social media.

• Asian Journal for Public Opinion Research
• /
• v.9 no.1
• /
• pp.48-82
• /
• 2021

This research article attempts to understand the current situation of fake news on social media in India. The study focused on four characteristics of fake news based on four research questions: subject matter, presentation elements of fake news, debunking tool(s) or technique(s) used, and the social media site on which the fake news story was shared. A systematic sampling method was used to select a sample of 90 debunked fake news stories from two Indian fact-checking websites, Alt News and Factly, from December 2019 to February 2020. A content analysis of the four characteristics of fake news stories was carefully analyzed, classified, coded, and presented. The results show that most of the fake news stories were related to politics in India. The majority of the fake news was shared via a video with text in which narrative was changed to mislead users. For the largest number of debunked fake news stories, information from official or primary sources, such as reports, data, statements, announcements, or updates were used to debunk false claims.

• Journal of Korea Multimedia Society
• /
• v.18 no.11
• /
• pp.1419-1426
• /
• 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.

• Asian Journal for Public Opinion Research
• /
• v.8 no.2
• /
• pp.105-125
• /
• 2020

The purpose of this paper is to analyze 1) who created and distributed fake news, 2) the distribution channels of fake news, 3) who fake news has targeted, and 4) the effects on voting and the impact of fake news on Korean politics. In South Korea, fake news was mainly created by candidates or election campaigns. The reason is that in the wake of the impeachment of President Park Guen Hye, all the political parties in Korea used fake news as a means of mobilizing supporters for each of their candidates or parties to gain an advantage in situations involving political divisions and confrontations between the pro-impeachment, progressive young generation and anti-impeachment, conservative senior generation. Voters' media usage patterns were polarized through social network services (SNS) media and television. Fake news was mostly received through these two media outlets. According to the spreading structure of fake news in Korea, the younger generation generally uses SNS posts intended for unspecified individuals, and the older generation uses closed SNS like KakaoTalk or Naver's BAND. In the end, it is typically characteristic of the older generation to spread fake news through existing offline human networks. In the 2017 presidential election, fake news has been confirmed to have the effect of mobilizing supporters for each political party. In the presidential election, an increase in voter turnout was confirmed among those in their 20s and those in their 60s or older. Evidently, fake news influenced the election of Moon Jae-In. The influence of fake news is expected to grow further as ideological polarization and consequent political polarization continues to intensify in South Korea.

• Proceedings of the IEEK Conference
• /
• 2007.07a
• /
• pp.287-288
• /
• 2007

In this paper, we propose a fake-iris detection method. In order to detect the fake-iris, we measure physiological features which are the reflectance ratio of the iris to the sclera at 750 nm and that at 850nm. In order to classify live and fake iris features, we use support vector data description (SVDD). From our experimental results, it is clear that our fake-iris detection method achieves high performance when distinguishing between a live-iris and a fake-iris.

• Journal of Korea Multimedia Society
• /
• v.24 no.12
• /
• pp.1624-1631
• /
• 2021

With the continued development of image processing technology, we live in a time when it is difficult to visually discriminate processed (or tampered) images from real images. However, as the risk of fake images being misused for crime increases, the importance of image forensic science for identifying fake images is emerging. Currently, various deep learning-based identifiers have been studied, but there are still many problems to be used in real situations. Due to the inherent characteristics of deep learning that strongly relies on given training data, it is very vulnerable to evaluating data that has never been viewed. Therefore, we try to find a way to improve generalization ability of deep learning-based fake image identifiers. First, images with various contents were added to the training dataset to resolve the over-fitting problem that the identifier can only classify real and fake images with specific contents but fails for those with other contents. Next, color spaces other than RGB were exploited. That is, fake image identification was attempted on color spaces not considered when creating fake images, such as HSV and YCbCr. Finally, dropout, which is commonly used for generalization of neural networks, was used. Through experimental results, it has been confirmed that the color space conversion to HSV is the best solution and its combination with the approach of increasing the training dataset significantly can greatly improve the accuracy and generalization ability of deep learning-based identifiers in identifying fake images that have never been seen before.