• Korean journal of communication and information
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• v.35
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• pp.362-393
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• 2006

The purpose of this manuscript was to investigate the effects of issue involvement and relation of perceivers to comparison targets on the magnitude of third person perceptions. The investigation was expected to help us to understand the underlying process of third person effect hypothesis. Data was collected from adult residents in Ohio, United States by telephone survey in 2003(n=524). Like most other third person effect studies, this study supported the hypothesis: Respondents perceived more media effects on others than themselves for both 'Negative media portrayals of smokers' and 'News coverage of Roman Catholic priest's sexual scandals'. Results of five hypothesis tests suggest that when relationship between a perceiver and a particular comparison target is present third person perception is explained more by cognitive components than motivational components. In this case, third person perception varies with comparison target's issue involvement while it is independent of social distance between the perceivers and the comparison target. Also, perceivers' issue involvement positively correlates with the magnitude of third person effect. Based on the results, it is concluded that when perceives or a comparison target is involved in a message cognitive processes accounting for the relationship can impact the magnitude of third person effect. An important theoretical implication of the study is that third person effect is, to some extent, related with framing effect and priming effect.

• The Journal of the Korea Contents Association
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• v.16 no.9
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• pp.726-738
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• 2016

This study selected the Marine Corps camp accident in 2013 as its subject and analyzed it in order to explore the relevance of media framing on discourse on the safety of outdoor experience activities. Data were collected from search sites provided by news coverage data from March 26, 2010 when the sinking of the South Korean Navy corvette Cheonan occurred in South Korea, which had seen a surge in Marine Corps experience camps, to July 21, 2013, a few days after the Marine Corps camp accident. Data about a total of 211 cases 138 cases before the Marine Corps camp accident, and 73 cases after the accident were inductively analyzed. According to the results, news coverages on the Marine Corps camp were largely divided into positive framing that glamorized outdoor experience activities before the accident and negative framing after the accident. To put it concretely, the framing before the accident tended to glamorize outdoor experience activity as the best educational program which helped the participants to enhance their patience and sense of independence through boot camp experience, thereby increasing their self-esteem and arousing their cooperative spirit as members of society. However, after the accident media framing tended to publicize insensitivity to safety. The media framing characterized by dualistic coverage is considered to be an obstacle to the spread of safety culture, which is required in South Korean society. Therefore, media need to maintain more cool-headed and objective attitudes when reporting news.

• Journal of Korea Multimedia Society
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• v.2 no.3
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• pp.231-242
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• 1999

Generally, either caption-based search method or content-based search methods is used to retrieve video information. However, each search method has its limitations. Caption-based search is apt to lose consistency as for user's subjects, and content-based search is hard to extract general means. To enhance efficiency and correctness as for complementing each other, we propose the Integrated Video Data Model(IVDM) which integrates the two search methods, to device the model, we analyze video data and construct the structure of video information hierarchically. IVDM supports caption-based search as assigning meta-data by analyzing thematic-unit in the higher level, and also supports content-based search as extracting feature data by analyzing the content of video data in the lower level. We design Object-Oriented database schema of news video, based-on the IVDM. And we provide 4-type of queries and query processing algorithm to retrieve news video information.

• Journal of Korea Multimedia Society
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• v.14 no.6
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• pp.730-741
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• 2011

With the development of the internet and computer technology, the amount of information through the internet is increasing rapidly and it is managed in document form. For this reason, the research into the method to manage for a large amount of document in an effective way is necessary. The conventional document categorization method used only the keywords of related documents for document classification. However, this paper proposed keyword extraction method of based on association rule. This method extracts a set of related keywords which are involved in document's category and classifies representative keyword by using the classification rule proposed in this paper. In addition, this paper proposed the preprocessing method for efficient keywords creation and predicted the new document's category. We can design the classifier and measure the performance throughout the experiment to increase the profile's classification performance. When predicting the category, substituting all the classification rules one by one is the major reason to decrease the process performance in a profile. Finally, this paper suggested automatically categorizing plan which can be applied to hierarchical category architecture, extended from simple category architecture.

• Journal of Korea Multimedia Society
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• v.12 no.3
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• pp.427-435
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• 2009

Users are able to search and read interesting items and hence click hyperlink linked to the item which is detailed content unit such as menu, login, news, video, etc. Small screen like mobile device is very difficult to viewing all web contents at once. Browsing and searching for interesting items by scrolling to left and right or up and down is discomfort to users in small screen. Searching and displaying directly the item preferred by users can reduces difficulty of interface manipulation of mobile device. To archive it, web contents based on desktop will be segmented on a per-item basis which component unit of web contents. Most segment algorithms are based on segment method through analysis of HTML code or mobile size. However, it is difficult to extract item blocks. Because present web content is getting more complicated and diversified in structure and content like web portal services. A web content segment algorithm suggested in this paper is based on extracting item blocks is component units of web contents.

• Journal of Korea Multimedia Society
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• v.23 no.2
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• pp.301-316
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• 2020

Algorithm journalism refers to the practices of automated news generation using algorithms that generate human sounding narratives. Algorithm journalism is known to have strengths in automating repetitive tasks through rapid and accurate analysis of data, and has been actively used in news domains such as sports and finance. In this paper, we propose an interactive card news system that generates personalized local election articles in 2018. The system consists of modules that collects and analyzes election data, generates texts and images, and allows users to specify their interests in the local elections. When a user selects interested regions, election types, candidate names, and political parties, the system generates card news according to their interest. In the study, we examined how personalized card news are evaluated in comparison with text and card news articles by human journalists, and derived implications on the potential use of algorithm in reporting political events.

• The KIPS Transactions:PartD
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• v.19D no.4
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• pp.271-280
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• 2012

Currently, contents generated by SNS services are increasing exponentially, as the number of SNS users increase. The SNS is commonly used to post personal status and individual interests. Also, the SNS is applied in socialization, entertainment, product marketing, news sharing, and single person journalism. As SNS services became available on smart phones, the users of SNS services can generate and spread the social issues and controversies faster than the traditional media. The existing indexing methods for web contents have limitation in terms of real-time indexing for SNS contents, as they usually focus on diversity and accuracy of indexing. To overcome this problem, there are real-time indexing techniques based on RDBMSs. However, these techniques suffer from complex indexing procedures and reduced indexing targets. In this regard, we introduce the TK-Indexing method to improve the previous indexing techniques. Our method indexes the generation time of SNS contents and keywords by way of NoSQL to indexing SNS contents in real-time.

• Smart Media Journal
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• v.6 no.1
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• pp.47-53
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• 2017

Social issues are important factors that decide government policy and newspapers are critical channels that reflect them. Analysing news articles can contribute to understanding social issues, but it is very difficult to analyse the unstructured large volumes of news data manually. Therefore, this study aims to analyze the different views among stakeholders of a specific social issue by using text analysis, word cloud analysis and associative analysis methods, which systematically transform unstructured news data into structured one. We analyzed a total of 115 news articles and a total of 6,772 comments, collected from the selected newspapers (Chosun-Il-bo, Joongang-Il-bo, Donga-Il-bo, Maeil Newspaper, Busan-Il-bo) for two weeks. We found that there are significant differences in tone between newspapers. While nation-wide daily newspapers focus on political relations with local areas, local daily newspapers tend to write articles to represent local governments' interests.

• Smart Media Journal
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• v.10 no.2
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• pp.38-47
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• 2021

This study analyzed media reports on the Address of Things, which are being introduced through the amendment of related law and pilot projects. The titles and its texts in the media's reports were collected by searching for 'Address of Things' on the Naver News Platform. Then, we analyzed the corpus using by topic modeling and network analysis. As a result, there were four topics: 'Promotion of the address of things system', Proof of assigning Address of Things', 'Improvement of usage of the Roadname Address Systems', and 'Education and public relation for the address activation'. It was confirmed that the topic 'Proof of assigning Address of Things' was the main agenda. We presented some implication by comparing the results with the 「3rd Basic Plan for Address Policy (2018-2022)」 of the Ministry of Public Administration and Security.

• Smart Media Journal
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• v.10 no.2
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• pp.16-21
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• 2021

Financial time series analysis plays a very important role economically and socially in modern society and is an important task affecting global development, but due to difficulties such as a lot of noise and uncertainty, financial time series analysis prediction is a difficult research topic. In this paper, we propose a market prediction method (MPIL) by converting unstructured data and structured data into images. For market prediction, it analyzes SNS and news data, which is unstructured data for n days, and converts the market data, which is structured data, to an image with the GADF algorithm, and predicts an ultra-short market that predicts the price of n+1 days through image learning. MPIL has an average accuracy of 56%, which is higher than the 50% average accuracy of the model that predicts the market with LSTM by using sentiment analysis used for existing market forecasting.