• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.579-585
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• 2023

The purpose of this study is to explore keywords within stalking-related news articles according to political orientation through the text network analysis, and then to examine the implicit intentions. Selecting total 1,607 articles including 824 articles of the conservative press(The Chosun Ilbo, The Joongang Ilbo) and 783 articles of the progressive press(The Hankyoreh, The Kyunghyang Shinmun) reported from January 1, 2018 to December 31, 2022, this study explored the aspect of topic category drawn through the topic modeling technique based on LDA(Latent Dirichlet Allocation). In the results of this study, the common topics of the conservative and progressive press were improvement of the perception of gender-based violence, personal protection & intensity of punishment, and disclosure of stalkers' personal information. Regarding the topics differently shown in those two press, the conservative press showed stalkers' harmful act, and outline of 'murder case at Sindang Station' while the progressive press showed request for aggravated punishment on the 'murder case at Sindang Station', and eradication of sexual exploitation crime (in cyber space). The results of this study imply that there are changes in the type of reporting according to ideological opinions about stalking in news articles.

• 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.

• Journal of Information Technology Services
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• v.13 no.3
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• pp.221-233
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• 2014

Because people's interest of the stock market has been increased with the development of economy, a lot of studies have been going to predict fluctuation of stock prices. Latterly many studies have been made using scientific and technological method among the various forecasting method, and also data using for study are becoming diverse. So, in this paper we propose stock prices prediction models using sentiment analysis and machine learning based on news articles and SNS data to improve the accuracy of prediction of stock prices. Stock prices prediction models that we propose are generated through the four-step process that contain data collection, sentiment dictionary construction, sentiment analysis, and machine learning. The data have been collected to target newspapers related to economy in the case of news article and to target twitter in the case of SNS data. Sentiment dictionary was built using news articles among the collected data, and we utilize it to process sentiment analysis. In machine learning phase, we generate prediction models using various techniques of classification and the data that was made through sentiment analysis. After generating prediction models, we conducted 10-fold cross-validation to measure the performance of they. The experimental result showed that accuracy is over 80% in a number of ways and F1 score is closer to 0.8. The result can be seen as significantly enhanced result compared with conventional researches utilizing opinion mining or data mining techniques.

• Korean Medical Education Review
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• v.19 no.3
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• pp.158-168
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• 2017

There is a more urgent call for educational methods of machine learning in medical education, and therefore, new approaches of teaching and researching machine learning in medicine are needed. This paper presents a case using machine learning through text analysis. Topic modeling of news articles with the keyword 'asbestos' were examined. Two hypotheses were tested using this method, and the process of machine learning of texts is illustrated through this example. Using an automated text analysis method, all the news articles published from January 1, 1990 to November 15, 2016 in South Korea which included 'asbestos' in the title and the body were collected by web scraping. Differences in topics were analyzed by structured topic modelling (STM) and compared by press companies and periods. More articles were found in liberal media outlets. Differences were found in the number and types of topics in the articles according to the partisanship and period. STM showed that the conservative press views asbestos as a personal problem, while the progressive press views asbestos as a social problem. A divergence in the perspective for emphasizing the issues of asbestos between the conservative press and progressive press was also found. Social perspective influences the main topics of news stories. Thus, the patients' uneasiness and pain are not presented by both sources of media. In addition, topics differ between news media sources based on partisanship, and therefore cause divergence in readers' framing. The method of text analysis and its strengths and weaknesses are explained, and an application for the teaching and researching of machine learning in medical education using the methodology of text analysis is considered. An educational method of machine learning in medical education is urgent for future generations.

• The Journal of the Korea Contents Association
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• v.17 no.8
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• pp.98-109
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• 2017

According to Peter Berger and Thomas Luckmann, people do not live understanding the objective existence, but live defining the reality that is socially constructed. This study analyzed the frame of news report dealing with public figures to inquire into the following subjects: Which group is defined as a public figure? Which role and obligation are required for a public figure? Which standard can be set to judge right and wrong of behavior of a public figure? The research result shows that the press mentioned with most frequency politicians and broadcasting-related people as public figures. In case of politicians, the press focuses most on scandals related to their duties and qualities, while in case of broadcasting-related people, the press focuses most on scandals relevant to ethical problems.

• The Korean Journal of Archival Studies
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• no.34
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• pp.107-163
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• 2012

The share of the internet has grown significantly in terms of usage and level of influence. Among the internet media, OhmyNews is considered a alternative media representing Korea's independent internet news, and a typical example displaying characteristics of the internet news. The processing step can be divided as five stage, with recorded information and applicable technical element extractable from each stage. In this thesis paper, we have analyzed domestic and overseas metadata standard examples to devise metadata design plans. Items to be focused when redesigning metadata based on domestic and foreign case studies are as follows: First, user access should be convenient; second, connection with related information should be considered; third, accumulation of production, management, usage, storage, and action history should be considered; and fourth, the design should allow higher utilization of contents. In depth researches over internet media are already being carried out in external academic disciplines including the media information studies, information and communication studies, and communications studies. We expect that it will also be necessary to consider such researches over the internet media for mass media record management research going forward.

• 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 Human Ecology
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• v.24 no.4
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• pp.513-529
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• 2015

This study performed corroborative analysis by establishing hypothesis so as to corroboratively define the effect on brand attitude of psychological risk recognition in the case where consumers reading negative media news related to bakery recognize crisis communication on the basis of which point. According to corroborative analysis, the role of psychological crisis perception as parameter is confirmed in the causal relation between crisis communication recognition and brand attitude. Such result of study confirms that the positive change in crisis communication recognition reduces psychological risk perception to bakery products and such psychological risk perception eventually become factor which affects brand attitude over products. Such result of study suggests that when reading negative media news on bakery, the influence on consumer's evaluation of news on the basis of certain point and the influence on the formation of causal relation between psychological risk perception and brand attitude has scientific ground. In the aspect, the main result of this study is to find the clue that when comparing precedent study between crisis communication recognition and brand attitude, psychological risk perception is realized with brand attitude as media by verifying the parameter role of psychological risk perception.

• Journal of Korea Multimedia Society
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• v.25 no.11
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• pp.1613-1620
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• 2022

Through previous studies, it was found that news from legacy media, including television, has an agenda-setting effect and priming effect on the perceptions and attitudes of audiences about politics and war, and that film media also has an agenda-setting effect and political priming effect on war issues. However, it is difficult to find studies on the effects of war-related TV documentaries on media audiences. Therefore, in this study, An experimental study was conducted to investigate whether there is a change in 'recognition of the importance of security', 'will for South-North Unification' and 'will to participate in war in case of emergency' for the audience who watched the KBS special <100 Days of Invasion of Ukraine, Part 1 into the Fire>. As a result of the analysis, it was found that watching a war-related TV documentary reinforced the audience's 'recognition of the importance of security' and 'will for South-North Unification'. However, it was confirmed that watching a war-related TV documentary did not strengthen the audience's will to participate in war in case of emergency.

• Journal of the Korean Society for information Management
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• v.39 no.1
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• pp.257-280
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• 2022

In this study, we analyzed comments on news articles of representative companies of the three industries (i.e., semiconductor, secondary battery, and bio industries) that had been listed as national strategic technology projects of South Korea to identify public opinions towards them. In addition, we analyzed the relationship between changes in public opinion and stock price. 'Samsung Electronics' and 'SK Hynix' in the semiconductor industry, 'Samsung SDI' and 'LG Chem' in the secondary battery industry, and 'Samsung Biologics' and 'Celltrion' in the bio-industry were selected as the representative companies and 47,452 comments of news articles about the companies that had been published from January 1, 2020, to December 31, 2020, were collected from Naver News. The comments were grouped into positive, neutral, and negative emotions, and the dynamic topics of comments over time in each group were analyzed to identify the trends of public opinion in each industry. As a result, in the case of the semiconductor industry, investment, COVID-19 related issues, trust in large companies such as Samsung Electronics, and mention of the damage caused by changes in government policy were the topics. In the case of secondary battery industries, references to investment, battery, and corporate issues were the topics. In the case of bio-industries, references to investment, COVID-19 related issues, and corporate issues were the topics. Next, to understand whether the sentiment of the comments is related to the actual stock price, for each company, the changes in the stock price and the sentiment values of the comments were compared and analyzed using visual analytics. As a result, we found a clear relationship between the changes in the sentiment value of public opinion and the stock price through the similar patterns shown in the change graphs. This study analyzed comments on news articles that are highly related to stock price, identified changes in public opinion trends in the COVID-19 era, and provided objective feedback to government agencies' policymaking.