• 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.

• Journal of Information Technology Services
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• v.18 no.1
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• pp.219-234
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• 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
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• v.9 no.1
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• pp.25-47
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• 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.

• International Journal of Knowledge Content Development & Technology
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• v.11 no.4
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• pp.35-51
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• 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
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• v.9 no.1
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• pp.48-82
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• 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.

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

• Journal of Information Technology Applications and Management
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• v.26 no.6
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• pp.1-12
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• 2019

On the Internet age, the news is generated and distributed not only by traditional news media, but also by a variety of online news media, news platforms, content websites/content farms, and social media. Since it is an easy task to create and distribute news, some of these news reports may contain fake or false facts. In the end, the cyberspace is full of fake or false messages. People may wonder if these fake news actually influence our decision making. In this paper, we discussed a real case of fake news. In this case, a Taiwanese company used some fake news, advertorial news, and news placement to manipulate or influence its stock price and trade volume. We collected all news for the case company during a period of four years and five months (from January 2013 to May 2017). We analyzed the relationship between published news and stock price. Based on the analysis results, we conclude that we should not ignore the influence of news placement and fake business news on the stock price.

• 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.

• Knowledge Management Research
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• v.20 no.2
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• pp.87-103
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• 2019

The purpose of this study was to explore the factors influencing acceptance (e.g., comprehension,) and diffusion of information recipients' by depending on the authenticity of news. Specifically, this study has examined the effects of the news contents(political vs. general), need for cognition(high vs. low) and authenticity of the News(real news vs. fake news) on both acceptance and diffusion of news. Based on previous work, this study has developed a conceptual model to present each research hypothesis and tested it by conducting experiments as the follows. As a result, according to the authenticity of the news and the contents of the news (political and general), the acceptance of political contents was high regardless of the authenticity of the news, and the acceptance of real news was higher than that of fake news. However, in the proliferation (comment), both the political contents and the general contents showed the characteristic of spreading (commenting) fake news rather than real news. contrary to this, the cognitive level did not show any significant difference in acceptance (understanding) and proliferation (comment, sharing, recommendation). This study provides academic implications in that it examines the influences of accepting (comprehension) and diffusion (comment, sharing, recommendation) of real news and fake news. It also provides practical implications for responding to fake news and new marketing strategies in an environment where contents are delivered through diverse social media.

• The Journal of Society for e-Business Studies
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• v.23 no.4
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• pp.19-39
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• 2018

Recently, fake news has attracted worldwide attentions regardless of the fields. The Hyundai Research Institute estimated that the amount of fake news damage reached about 30.9 trillion won per year. The government is making efforts to develop artificial intelligence source technology to detect fake news such as holding "artificial intelligence R&D challenge" competition on the title of "searching for fake news." Fact checking services are also being provided in various private sector fields. Nevertheless, in academic fields, there are also many attempts have been conducted in detecting the fake news. Typically, there are different attempts in detecting fake news such as expert-based, collective intelligence-based, artificial intelligence-based, and semantic-based. However, the more accurate the fake news manipulation is, the more difficult it is to identify the authenticity of the news by analyzing the news itself. Furthermore, the accuracy of most fake news detection models tends to be overestimated. Therefore, in this study, we first propose a method to secure the fairness of false news detection model accuracy. Secondly, we propose a method to identify the authenticity of the news using the social data broadly generated by the reaction to the news as well as the contents of the news.