• Korean Journal of Legislative Studies
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• v.27 no.3
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• pp.155-188
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• 2021

This study examines dynamics in election news making. It is important to understand when and how news media produce election news in order to grasp news making and voting behavior. The news media sometimes make election news by focusing on issues and policies. Often they frame elections as a game and focus on election strategies while covering elections. This article argues that as time goes by during the election period, the number of policy news tends to decrease while the frequency of strategic news is likely to increase. Also, TV's and newspapers show distinctive patterns of election news making. In order to examine the arguments, this study categorizes election news stories into policy and strategic news stories produced during the 2020 Korean congressional elections and constructs daily time-series data of them. The results of structural break and regression analyses partially support the arguments.

• The Journal of the Korea Contents Association
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• v.14 no.10
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• pp.472-485
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• 2014

This study focuses on the news making system of the prime time news of PSB in Korean society, where the presence of ethnic minorities is increasing rapidly. Although the World Wide Web has become one of the most attractive media over the last decade, Korean PSB, Korean Broadcasting System (KBS), still remains the most popular and influential medium. Therefore, the process of analyzing news making system of ethnic minorities in Korean society represented in Korean PSB as a social construction is meaningful in that it provides an important key to understand the cultural and political background and characteristics of society. For this purpose, the article tries to understand news making process when producing news related to ethnic minorities in the Korean society such as migrant workers, married migrant women and mixed-heritage children of multicultural families by interview with ten reporters in KBS. As a result, most KBS reporters had stereotypes towards multiculturalism and migrants and news reports relating to ethnic minorities are usually produced routinely, using a set of rules that have become part of KBS culture.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.143-156
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• 2012

People easily believe that news and stock index are closely related. They think that securing news before anyone else can help them forecast the stock prices and enjoy great profit, or perhaps capture the investment opportunity. However, it is no easy feat to determine to what extent the two are related, come up with the investment decision based on news, or find out such investment information is valid. If the significance of news and its impact on the stock market are analyzed, it will be possible to extract the information that can assist the investment decisions. The reality however is that the world is inundated with a massive wave of news in real time. And news is not patterned text. This study suggests the stock-index invest model based on "News Big Data" opinion mining that systematically collects, categorizes and analyzes the news and creates investment information. To verify the validity of the model, the relationship between the result of news opinion mining and stock-index was empirically analyzed by using statistics. Steps in the mining that converts news into information for investment decision making, are as follows. First, it is indexing information of news after getting a supply of news from news provider that collects news on real-time basis. Not only contents of news but also various information such as media, time, and news type and so on are collected and classified, and then are reworked as variable from which investment decision making can be inferred. Next step is to derive word that can judge polarity by separating text of news contents into morpheme, and to tag positive/negative polarity of each word by comparing this with sentimental dictionary. Third, positive/negative polarity of news is judged by using indexed classification information and scoring rule, and then final investment decision making information is derived according to daily scoring criteria. For this study, KOSPI index and its fluctuation range has been collected for 63 days that stock market was open during 3 months from July 2011 to September in Korea Exchange, and news data was collected by parsing 766 articles of economic news media M company on web page among article carried on stock information>news>main news of portal site Naver.com. In change of the price index of stocks during 3 months, it rose on 33 days and fell on 30 days, and news contents included 197 news articles before opening of stock market, 385 news articles during the session, 184 news articles after closing of market. Results of mining of collected news contents and of comparison with stock price showed that positive/negative opinion of news contents had significant relation with stock price, and change of the price index of stocks could be better explained in case of applying news opinion by deriving in positive/negative ratio instead of judging between simplified positive and negative opinion. And in order to check whether news had an effect on fluctuation of stock price, or at least went ahead of fluctuation of stock price, in the results that change of stock price was compared only with news happening before opening of stock market, it was verified to be statistically significant as well. In addition, because news contained various type and information such as social, economic, and overseas news, and corporate earnings, the present condition of type of industry, market outlook, the present condition of market and so on, it was expected that influence on stock market or significance of the relation would be different according to the type of news, and therefore each type of news was compared with fluctuation of stock price, and the results showed that market condition, outlook, and overseas news was the most useful to explain fluctuation of news. On the contrary, news about individual company was not statistically significant, but opinion mining value showed tendency opposite to stock price, and the reason can be thought to be the appearance of promotional and planned news for preventing stock price from falling. Finally, multiple regression analysis and logistic regression analysis was carried out in order to derive function of investment decision making on the basis of relation between positive/negative opinion of news and stock price, and the results showed that regression equation using variable of market conditions, outlook, and overseas news before opening of stock market was statistically significant, and classification accuracy of logistic regression accuracy results was shown to be 70.0% in rise of stock price, 78.8% in fall of stock price, and 74.6% on average. This study first analyzed relation between news and stock price through analyzing and quantifying sensitivity of atypical news contents by using opinion mining among big data analysis techniques, and furthermore, proposed and verified smart investment decision making model that could systematically carry out opinion mining and derive and support investment information. This shows that news can be used as variable to predict the price index of stocks for investment, and it is expected the model can be used as real investment support system if it is implemented as system and verified in the future.

• Korean journal of communication and information
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• v.32
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• pp.295-332
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• 2006

This study inquires at behavior and attitude of gatekeepers at major Korean media in the process of selecting and covering newsmakers, with focusing on factors, paths and practices in making news on the people. The study assumes that gatekeepers' social networking process with social elites, based on birth places, alma mater and kinship, plays great role in making people in the news. The study applies methods of in-depth interviews with people-page gatekeepers and content analysis of news on newsmakers. The in-depth interviews and content analysis unveil that people-page gatekeepers tend to support high society and social elite group. Furthermore, through the process of news-making, the gatekeeper group shares social capital such as economic exchanges and socio-political influences with social elite group. The result of interviews and analysis confirm that social networking based on personal affiliation plays as an important factor in selecting and covering newsmakers. With in-depth analysis of news contents, the study finds out that social elite groups of top government officials, corporate CEOs, medical doctors, lawyers, judges, prosecutors, college professors, cultural celebrities and journalists, who are predominantly male, appear on people pages much frequently out of proportion. The content analysis also reveal that 'personal news,' which cover personal and private life or unilaterally promote newsmakers predominate in terms of frequency and amount over socially-important or pubic-interested 'public news.' In terms of news values, fragmentary news composed of sensational, personal and gossiping elements appear more frequently than socially-meaningful news with strong social issues and public messages.

• 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.

• 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.

• Korean journal of communication and information
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• v.66
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• pp.5-27
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• 2014

The past, present, and future of online journalism in Korea are inextricably bound up with the portal site news services. In traditional journalism, finite news media took hold on news consumption completely because of performing news production and distribution simultaneously. Since then, in the age of multi-media and multi-channel, the audience selection has become more important because of greatly increasing news media and then exploding news production. In online journalism, the news distribution have emerged as the most important field because of the intensive consuming the portal site news services making use of various news easier, the characteristic of news consumption focusing on not news media brands but news media contents, etc. Therefore, the news present landscape of Korean journalism oriented news distribution has been completed by that the portal site news services became the symbol of online journalism. That the portal site news services performing only news distribution have more influence than the paper based online newspapers and Internet based online newspapers producing news means the change of media power. By this, a conflict between news media and portal site news services appears at all times.

• Journal of Korea Multimedia Society
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• v.23 no.8
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• pp.1049-1058
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• 2020

'Instagrammable' is a new term which means a photo or a series of pictures are worth posting on Instagram. Since Instagram is an image-oriented social media platform, it is important to give users proper awareness through images in order to be an instagrammable post. In this study, we explored the proper delivery method of messages within instagrammable posts through the use of hashtags(#). Specifically, we paid attention to the use of 'Card News', which involves a series of images that form a short narrative. Hashtags play an important role that they often describe sharing intention of the post, and we found analyzing the use of hashtags in Card News posts is a good indicator of users' Instagram activities. Currently, there are more than 580k posts are found with the search keyword Card News, and the number is increasing. In this study, we collected and analyzed more than 50k hashtags on Instagram to explore how news stories are posted from both the general users and news media accounts. Furthermore, we conducted interviews with journalists to analyze how news media are making use of Instagram as a legitimate place to share news stories with impact.

• 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.

• Journal of Korea Multimedia Society
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• v.22 no.11
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• pp.1313-1323
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• 2019

With the development of the Internet and the increase of smart phones, various services considering user convenience are increasing, so that users can check news in real time anytime and anywhere. However, online news is categorized by media and category, and it provides only a few related search terms, making it difficult to find related news related to keywords. In order to solve this problem, we propose a method to recommend related documents more accurately by applying Doc2Vec similarity to the specific keywords of news articles and weighting the title and contents of news articles. We collect news articles from Naver politics category by web crawling in Java environment, preprocess them, extract topics using LDA modeling, and find similarities using Doc2Vec. To supplement Doc2Vec, we apply TF-IDF to obtain TC(Title Contents) weights for the title and contents of news articles. Then we combine Doc2Vec similarity and TC weight to generate TC weight-similarity and evaluate the similarity between words using PMI technique to confirm the keyword association.