A STUDY ON ARTIFICIAL INTELLIGENCE ALGORITHM FOR DETERMINING FAKE NEWS CONTAINING FACTS AND VALUE ORIENTATION OF NEWS

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1 International Journal of Civil Engineering and Technology (IJCIET) Volume 9, Issue 11, November 2018, pp , Article ID: IJCIET_09_11_181 Available online at ISSN Print: and ISSN Online: IAEME Publication Scopus Indexed A STUDY ON ARTIFICIAL INTELLIGENCE ALGORITHM FOR DETERMINING FAKE NEWS CONTAINING FACTS AND VALUE ORIENTATION OF NEWS Dhaekyou KIM National Information Society Agency, Seoul, Korea Jang Mook Kang* Department of Big-Data Industrial Security, NamSeoul University, Cheonan-city 31020, Korea *Corresponding Author honukang@gmail.com ABSTRACT Fake news is a type of yellow journalism or propaganda that consists of deliberate misinformation or hoaxes spread via traditional print and broadcast news media or online social media. You can find social meaning by gathering data that is not related at all. It is the big data analysis. At the same time, however, data that does not really matter can be collected and made into fake news. Big data analysis is used maliciously. This study deals with the current status of fake news in politics and economics in Korea. And the process of production, sharing, and spread of fake news. This can help you understand the impact of fake news on the Internet ecosystem. It is also expected to give insight into how to block or reduce fake news. Key words: Fake News, Artificial Intelligence Algorithm, Big Data, Fake News Production Mechanism Cite this Article: Dhaekyou KIM, Jang Mook Kang, A Study on Artificial Intelligence Algorithm for Determining Fake News Containing Facts and Value Orientation of News, International Journal of Civil Engineering and Technology (IJCIET) 9(11), 2018, pp INTRODUCTION In Korea, fake news is a big problem. This is because false facts are circulated every year in elections to elect a member of the National Assembly, the Mayor, etc. Not only that. There is a false belief that the presidential election will spread false news and will not be punished if elected. Fake news is a type of yellow journalism or propaganda that consists of deliberate misinformation or hoaxes spread via traditional print and broadcast news media or online social media [1] editor@iaeme.com

2 Dhaekyou KIM, Jang Mook Kang In Korea, Naver( takes the majority of the search engine market as a portal. In particular, Naver has a leading edge in news search. Naver 's news coexists with the automation part by the algorithm and the passive area by the human. During the presidential election, Naver has been suspicious of manipulation in real-time query rankings and comments. Fake news is written and published with the intent to mislead in order to damage an agency, entity, or person, and/or gain financially or politically,[2] often using sensationalist, dishonest, or outright fabricated headlines to increase readership, online sharing, and Internet click revenue. In the latter case, it is similar to sensational online "clickbait" headlines and relies on advertising revenue generated from this activity, regardless of the veracity of the published stories [3]. This research relates to a system for determining whether or not a fake news is available. News is a case where the fact is true or false. If the fact is false, it can be judged as a fake news. However, when political interests are mixed, values are included. When values are included, it is not easy to distinguish between true and false. If the value is included, a qualitative judgment should be made. This study describes the process of efficiently handling quantitative and qualitative evaluation for a fake news. 2. FAKE NEWS STATUS AND ANALYSIS METHOD 2.1. Fake News Status The South Korean journalists and media experts lament political hostility between Korea's which distorts Media coverage of North Korea [4]. The Republic of Korea is suffering from fake news in various parts, such as the relationship between South Korea and North Korea, entertainer 's case. In order to discover fake news, the Chosun Ilbo in Korea also developed a fact diagnosis service. The picture below is a fact diagnosis service developed by Chosun Ilbo. Figure 1. The Fact Check in Chosun News [5] The fact check of Chosun Ilbo is not based on artificial intelligence. Most facts are reported manually. Therefore, labor costs are necessary for continuous fact check. In addition, the Chosun Ilbo, which developed this system, is a representative conservative medium. It is difficult to ensure neutrality of the medium. In Korea, when fake news became a social issue, various research institutes and universities conducted research on it. The following figure is a fact check service developed by Seoul National University Press Information Research Center editor@iaeme.com

3 A Study on Artificial Intelligence Algorithm for Determining Fake News Containing Facts and Value Orientation of News Figure. 2. The Fact Check in SNU [6] The fact check system developed by Seoul National University has the following process. First, only 'facts' such as factual statements should be verified, and ideas and opinions should be excluded from the verification subject. Second, the basis of the verification should be based on objective information and the reality should be judged according to clear criteria. Third, the issues related to the fact check are complied with "Code of Ethics and Code of Practice" of the Korean Press Association. In particular, when writing content related to election polls, the Korean Press Association's "Rules of Press Public Opinion Survey" are followed. Fourth, affiliated media companies can modify SNU FactCheck posts if they need to be corrected for factual errors, supplementary data, typo corrections, etc. However, when a journalist modifies a post, the editorial history of the journalist and the reasons for modification are left open to the user. Fifth, when a press uploads a verification that you want to check facts, a badge is created. Other media can add verification and judgment results to the badge. Sixth, if two or more media are involved in the verification of a fact and there are more than three steps in the judgment result (eg facts vs. not facts), it will be marked as 'disputed'. The above process can confirm fact or fact by user participation. However, this process consumes another debate and manpower as much as the Korea Media Arbitration Commission. Therefore, it is necessary to judge fake news based on artificial intelligence Analysis Method of Fake News The way to analyze fake news is largely divided into qualitative and quantitative methods. Quantitative methods are mostly based on manual work. There is no developed software because the qualitative part actually has to be judged value. Relying only on social media news has caused major issues for many young people who have difficulty determining the credibility of news sources. A recent study by Stanford University of nearly 8,000 students (from grammar school through college) tested their ability to tell news from ads and to discern websites from hate groups and mainstream professional organizations editor@iaeme.com

4 Dhaekyou KIM, Jang Mook Kang Figure. 2. Foreground of News [7] They found that most Students don t know when news is fake and cannot accurately determine the credibility of news sources. The above picture shows media such as various news. Each medium is conservative or liberal. It is easy to find things that are not true. However, it is difficult to establish justice. Justice has value. This value depends on the group to which the people belong. For example, Buddhism is a heresy religion for Christians. Buddhist values, on the other hand, are absolute. The direction that this value implies is important. What is justice in Buddhist values? What is justice in Christian values? Is it possible to judge the value like this? Does the news convey value? Or does it just tell the truth? In the next section, we review the virtuous cycle structure. 2.3 A Virtuous Circle Structure of Fake News and Fact News Table 1. Major themes on the future of the Fake News [8] editor@iaeme.com

5 A Study on Artificial Intelligence Algorithm for Determining Fake News Containing Facts and Value Orientation of News The following is the pew Internet Research Center results on the virtuous cycle of fake news. This article is an in-depth interview about fake news, miss information, and the meaning of truth. The problem of fake news is a matter of search and placement(layout) of news articles in the portal. In the future, the raw Data provided by the Internet of Things will develop into a problem of trust when it is converted into social meaning. Table 1 is a precondition for becoming a virtuous cycle of fake news. In order to reduce fake news, the problem mentioned in the above table should be solved. In order to solve the problems of information abuse, misunderstanding, fake, and truth in the new environment of connected society, efforts for implementing environment like the above table 1 are required 3. RESULTS AND DISCUSSION 3.1. Artificial Intelligence Algorithm The AI-based model can take various forms: it can be an artificial neural network (ANN), or a fuzzy-neural network etc. and there is also the possibility of using different types of speed tuning signals [9]. In the Internet environment of things, fake news algorithms can be designed around devices. In terms of software, we can use the result of analysis of social network service. Some of the most common examples of machine learning are Netflix s algorithms to make movie suggestions based on movies you have watched in the past or Amazon s algorithms that recommend books based on books you have bought before [10]. Machine learning algorithms can be divided into 3 broad categories supervised learning, unsupervised learning, and reinforcement learning. Supervised learning is useful in cases where a property (label) is available for a certain dataset (training set), but is missing and needs to be predicted for other instances. Unsupervised learning is useful in cases where the challenge is to discover implicit relationships in a given unlabeled dataset (items are not preassigned). Reinforcement learning falls between these 2 extremes there is some form of feedback available for each predictive step or action, but no precise label or error message [10, 15,16]. Of the various algorithms described above, value-oriented algorithms are described in the following paragraphs Value Orientation of decision for fake news News has value. Normal news only confirms facts. But even if it is true, its meaning changes when you analyze the value. So analyzing value is an important attempt to reveal the truth of the news. It is because the news is truth and it is trusted. The figure below describes the impact reduction from fake news. Figure.3. Fake News vaccine [11] editor@iaeme.com

6 Dhaekyou KIM, Jang Mook Kang This lead to the idea that it may be possible to develop a mental vaccine. Several European countries have started to fine social media companies for failing to remove defamatory fake news. Facebook has partnered with independent factcheckers to help flag disputed content. Google is demoting fake news in their search results [11, 12,13, 14]. 4. CONCLUSIONS This study analyzed the qualitative impact of fake news. Of course, fake news is news that is not true. At the same time, fake news has political or economic reasons. Therefore, it is necessary to analyze the motivation and sharing path of complex news production. This article was written to find value-oriented problems that include fake news. Through this research, we hope to have more qualitative approach besides quantitative solution of fake news. ACKNOWLEDGMENTS Funding for this paper was provided by Namseoul university. REFERENCES [1] Leonhardt, David, Thompson, Stuart A., "Trump's Lies". New York Times, June 23, 2017, Retrieved June 23, 2017 ( [2] Hunt, Elle, "What is fake news? How to spot it and what you can do to stop it". The Guardian, December 17, 2016, Retrieved January 15, 2017 ( [3] Schlesinger, Robert, "Fake News in Reality". U.S. News & World Report, April 14, 2017, Retrieved January 15, 2018 ( [4] H. Allcott; M.Gentzkow, "Social Media and Fake News in the 2016 election", Journal of Economic Perspectives. 31 (2), 2017, pp Retrieved Jan 3, ( [5] Retrieved Jan 1, ( [6] Retrieved Jan 2, ( [7] Retrieved Jan 6, ( [8] Janna Anderson, Lee Rainie, The Future of Truth and Misinformation Online, The Future of Truth and Misinformation Online, Pew Research Center, Oct. 2017, Retrieved Jan 20, 2018.( [9] Peter Vas, Artifical-intelligence-based electrical machines and drives, OUP Oxford, 1999, p. 434 [10] James Le, The 10 Algorithms Machine Learning Engineers Need to Know, KDnuggets, aug.2016, Retrieved Jan 21, 2018.( [11] Sander van der Linden, Beating the Hell Out of Fake News, A THINKING ON SUNDAY LECTURE, Ethical Record, 7 May 2017, Retrieved Jan 11, 2018.( [12] Udoh, G. (2017). An Aesthetic Appraisal of Newspaper Coverage of Boko Haram Activities. Journal of New Media and Mass Communication, 4(1), editor@iaeme.com

7 A Study on Artificial Intelligence Algorithm for Determining Fake News Containing Facts and Value Orientation of News [13] Ashong, A. C., & Henry, O. C. (2017). Content Preference among Online and Hardcopy Newspaper Readers in Imo State. Journal of New Media and Mass Communication, 4(1), [14] Nazmi, N. F. M., Ab Rashid, R., Zani, N. A. M., Jabar, N. F. A., & Aziz, M. F. (2018). Discourse Analysis on International Online News Reports of Manchester Bombing. International Journal of Asian Social Science, 8(9), [15] Rugai, J., & Hamiliton-Ekeke, J. T. (2016). A Review of Digital Addiction: A Call for Safety Education. Journal of Education and e-learning Research, 3(1), [16] Zhang, W. B. (2018). Endogenous Economic Growth with Education Subsidies. International Journal of Emerging Trends in Social Sciences, 2(1), z editor@iaeme.com