• Korean Journal of Human Ecology
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• v.19 no.1
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• pp.149-156
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• 2010

TV news anchor woman's appearance, voice, expression, and clothing, etc., have an influence on the reliability of the article to be reported. Among these, clothing is the most crucial factor in forming an anchor woman's image, especially the clothing color factor. This study is aimed at providing the basic foundation for anchor woman when they select the clothing color by analyzing the clothing color image on the screen. For this purpose, the KBS and MBC 9 o'clock news desk and SBS 8 o'clock news of the local major news programs were selected. With the collection of 300 pieces of news clips related to anchor woman's clothing from January to December 2008, they were classified into F/W seasons and analyzed by the clothing color. The surveying method of clothing color was to capture the anchor woman's clothing among the news clips, then pick the representing color by applying Adobe Photoshop, and researching the formed $L^*a^*b^*$ value of color chips. The surveyed color was transformed into value of distant cell, H V/C, and the results were analyzed. As a result, it showed that the White system for anchor woman's clothing during the S/S seasons is most frequently picked, followed by the Red system. In F/W seasons, Gray system is the most favored, then White and Red, respectively. It was revealed that the most frequently selected colors for upper-wear by anchor women in the three broadcasting stations was an achromatic color, such as White or Gray, and then the chromatic color, Red. It shows that there is no big difference in season. The Inner-wear color matched the jackets which were also achromatic in color, white and black being the most favored in the S/S seasons, and in the case of chromatic colors, Red was the most favored. In addition to this, identical coloration with jacket, coloration with similar color, or single color as clothing color were no less frequently adopted. During the F/W seasons, identical coloration accounts for 26%, the most popular colored being White and Red. It was found that the coloration with achromatic colors are highly favored in the three major broadcasting stations alike.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.3
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• pp.154-161
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• 2018

This study conducted to predict the stock market prices based on the assumption that internet news articles might have an impact and effect on the rise and fall of stock market prices. The internet news articles were tested to evaluate the accuracy by comparing predicted values of the actual stock index and the forecasting models of the companies. This paper collected stock news from the internet, and analyzed and identified the relationship with the stock price index. Since the internet news contents consist mainly of unstructured texts, this study used text mining technique and multiple regression analysis technique to analyze news articles. A company H as a representative automobile manufacturing company was selected, and prediction models for the stock price index of company H was presented. Thus two prediction models for forecasting the upturn and decline of H stock index is derived and presented. Among the two prediction models, the error value of the prediction model (1) is low, and so the prediction performance of the model (1) is relatively better than that of the prediction model (2). As the further research, if the contents of this study are supplemented by real artificial intelligent investment decision system and applied to real investment, more practical research results will be able to be developed.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.649-657
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• 2011

This study examines how news media covers Jang Ja-Yeon's scandal through analyzing texts and images about Jang Ja-Yeon described in SBS (Seoul Broadcasting System) Eight O'clock News. The study found that the news stories mainly covered lasciviously Jang Ja-Yeon's entertaining service, sexual service, other actresses who were forced to provide entertaining service, a list of people who forced her to serve, death, and vengeance. In addition, Jang Ja-Yeon in the news stories were described as "unknown actress," and she was located into low class and entertained the men in power. The analysis implicated that the body image of actress reflects a merchandize in the news media, and the news media used Ja-Yeon Jang's body image for news value which represents the society of reification, hierarchical and masculine society.

• The Journal of the Korea Contents Association
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• v.17 no.9
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• pp.510-522
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• 2017

This study aims to investigate the brand image of Korean TV news in terms of functional and symbolic attributes, to examine their interrelationships and their effect on audience' viewing intentions. A survey was conducted on 412 evening main news viewers of KBS1, SBS, and JTBC, and factor analysis and regression analysis were used. The results show that TV news brand personality was composed of three dimensions including enterprising, sincerity, and tradition. JTBC showed the highest mean value in terms of enterprising and sincerity over SBS and KBS1, and the lowest in tradition. The symbolic and functional attributes of the TV news brand image are highly correlated. Finally, the viewing intentions were determined in the order of news brand functional benefit, sincerity and enterprising personality factor.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.9
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• pp.1275-1278
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• 2021

Nowadays, fake news from newspapers and social media is a serious issue in news credibility. Some of machine learning methods (such as LSTM, logistic regression, and Transformer) has been applied for fact checking. In this paper, we present Transformer-based fact checking model which improves computational efficiency. Locality Sensitive Hashing (LSH) is employed to efficiently compute attention value so that it can reduce the computation time. With LSH, model can group semantically similar words, and compute attention value within the group. The performance of proposed model is 75% for accuracy, 42.9% and 75% for Fl micro score and F1 macro score, respectively.

• 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.

• Journal of Family Relations
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• v.22 no.4
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• pp.107-134
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• 2018

Objectives: The purpose of this study is to have diachronic understanding of holiday stress that has become the social issues through the analysis on the news articles about holiday stress from 1993 to 2016. Method: For this purpose, 416 articles and 457 cases about holiday stress from 5 daily newspapers such as Chosun Ilbo, Joongang Ilbo, Dong-A, Hankyoreh and Kyunghyang Shinmun etc. have been analyzed, conducting the qualitative and quantitative analysis together. Results: Firstly, the articles on holiday stress have been increased, showing the rapid increase per year for the last 20 years. It is presumed to be closely related to the socio-economic situation. Second, although there have been 'married women' overwhelmingly as the subject of holiday stress, the frequency of the young generation has been increasing recently including the 'married women'. Third, the 96.7% of the contents from psychological appeal appeared in the case of holiday stress is related to family values. Especially, the holiday stress related to 'value of patriarchy' was the biggest stress. However, there has been increasing holiday stress caused by 'value of kinship' and 'value of marriage' recently. Forth, as a countermeasure against the holiday stress, the 'perception on the change of family values' has been quantitatively suggested and it has become actively appeared in terms of contents after mid-2000s. However, it has been appeared low in terms of quantity and content recently. Conclusions: This study has significance since it has been verified that the holiday stress started from 'married women' but it has been expanded to the young generation and it is related to the change and co-existence of family values of our society.

• 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 Intelligence and Information Systems
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• v.19 no.3
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• pp.57-71
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• 2013

Over a billion people in the world generate new news minute by minute. People forecasts some news but most news are from unexpected events such as natural disasters, accidents, crimes. People spend much time to watch a huge amount of news delivered from many media because they want to understand what is happening now, to predict what might happen in the near future, and to share and discuss on the news. People make better daily decisions through watching and obtaining useful information from news they saw. However, it is difficult that people choose news suitable to them and obtain useful information from the news because there are so many news media such as portal sites, broadcasters, and most news articles consist of gossipy news and breaking news. User interest changes over time and many people have no interest in outdated news. From this fact, applying users' recent interest to personalized news service is also required in news service. It means that personalized news service should dynamically manage user profiles. In this paper, a content-based news recommendation system is proposed to provide the personalized news service. For a personalized service, user's personal information is requisitely required. Social network service is used to extract user information for personalization service. The proposed system constructs dynamic user profile based on recent user information of Facebook, which is one of social network services. User information contains personal information, recent articles, and Facebook Page information. Facebook Pages are used for businesses, organizations and brands to share their contents and connect with people. Facebook users can add Facebook Page to specify their interest in the Page. The proposed system uses this Page information to create user profile, and to match user preferences to news topics. However, some Pages are not directly matched to news topic because Page deals with individual objects and do not provide topic information suitable to news. Freebase, which is a large collaborative database of well-known people, places, things, is used to match Page to news topic by using hierarchy information of its objects. By using recent Page information and articles of Facebook users, the proposed systems can own dynamic user profile. The generated user profile is used to measure user preferences on news. To generate news profile, news category predefined by news media is used and keywords of news articles are extracted after analysis of news contents including title, category, and scripts. TF-IDF technique, which reflects how important a word is to a document in a corpus, is used to identify keywords of each news article. For user profile and news profile, same format is used to efficiently measure similarity between user preferences and news. The proposed system calculates all similarity values between user profiles and news profiles. Existing methods of similarity calculation in vector space model do not cover synonym, hypernym and hyponym because they only handle given words in vector space model. The proposed system applies WordNet to similarity calculation to overcome the limitation. Top-N news articles, which have high similarity value for a target user, are recommended to the user. To evaluate the proposed news recommendation system, user profiles are generated using Facebook account with participants consent, and we implement a Web crawler to extract news information from PBS, which is non-profit public broadcasting television network in the United States, and construct news profiles. We compare the performance of the proposed method with that of benchmark algorithms. One is a traditional method based on TF-IDF. Another is 6Sub-Vectors method that divides the points to get keywords into six parts. Experimental results demonstrate that the proposed system provide useful news to users by applying user's social network information and WordNet functions, in terms of prediction error of recommended news.

• Journal of Korea Trade
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• v.24 no.6
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• pp.61-81
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• 2020

Purpose - This paper examines how the consumer animosity of partner country influences the purchase of foreign products. We analyzed news sentiment to determine whether Chinese consumer's animosity affect the purchase of the products made in Korea around the time when the U.S. Terminal High Altitude Area Defense missile system was deployed in South Korea. Design/methodology - To measure the tone of Chinese consumer animosity more carefully, we utilized a text mining technique of the Chinese language to read the public's opinion. Using Chinese news paper's editorials of 2015.1-2018.10, we analyzed the sentiment toward Korea and regressed it with Korean export to China. Findings - Empirical results report that Chinese consumers tended to reduce their purchase of consumer goods from Korea when the animosity increased, that is, the sentiments of Chinese news editorials were negative. In contrast, the animosity did not affect the purchase of Korean intermediates or raw materials. We further analyzed the effect by dividing the animosity into three categories; politics, economics, and culture. Among these groups, political news exhibits a unique effect on Chinese purchase on consumer goods from Korea. Originality/value - Existing literature on animosity models has measured the animosity by collecting the consumers' opinions through survey at a given time point, whereas it is measured by analyzing the tone of the press release by sentiment analysis during the time period around the event occurrence in this study.