• The Journal of Bigdata
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• v.4 no.2
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• pp.23-34
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• 2019

Recently, the crime that utilizes the digital platform is continuously increasing. About 140,000 cases occurred in 2015 and about 150,000 cases occurred in 2016. Therefore, it is considered that there is a limit handling those online crimes by old-fashioned investigation techniques. Investigators' manual online search and cognitive investigation methods those are broadly used today are not enough to proactively cope with rapid changing civil crimes. In addition, the characteristics of the content that is posted to unspecified users of social media makes investigations more difficult. This study suggests the site-based collection and the Open API among the content web collection methods considering the characteristics of the online media where the infringement crimes occur. Since illegal content is published and deleted quickly, and new words and alterations are generated quickly and variously, it is difficult to recognize them quickly by dictionary-based morphological analysis registered manually. In order to solve this problem, we propose a tokenizing method in the existing dictionary-based morphological analysis through WPM (Word Piece Model), which is a data preprocessing method for quick recognizing and responding to illegal contents posting online infringement crimes. In the analysis of data, the optimal precision is verified through the Vote-based ensemble method by utilizing a classification learning model based on supervised learning for the investigation of illegal contents. This study utilizes a sorting algorithm model centering on illegal multilevel business cases to proactively recognize crimes invading the public economy, and presents an empirical study to effectively deal with social data collection and content investigation.

• Korean Journal of Legislative Studies
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• v.24 no.1
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• pp.135-170
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• 2018

The recent success of populist parties and candidates in the US and European countries leads to a massive amount of empirical research on populism, a deviant form of representative democracy. Much ink has been spilled to define populism and to identify the causes of its rise and continued success in democratic political system. However, little is known about populist attitudes of individual voters. Using a large-scale online survey fielded in the context of the South Korean presidential election in 2017, this study examines (1) what determines populist attitudes of South Korean voters and (2) how populist attitudes are associated with evaluations of political parties, candidates, and political issues. Statistical analysis reveals that people high on populism are more likely to support an underdog left-wing political party and its presidential candidate, and are less likely to support policies implemented or proposed under the auspices of the Park Geun-hye administration. These findings do not necessarily suggest the inherent affinity between populism and left-wing ideology; rather, it implies populist attitudes happened to appear in 2017, in reactions to lack of confidence in the previous government.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.559-564
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• 2021

The purpose of this study is to explore the factors that affect the intention to run remote classes after COVID-19 with university professors have fully experienced remote classes due to COVID-19. The research questions are what are the factors and the combinations of factors that affect the intention to run remote classes in the post-COVID-19. Data were collected through a survey of 311 remote classes at S Univ. in Seoul in fall 2020, and individuals and combinations of factors were confirmed through logistic regression analysis and decision tree analysis. As a result, individual factors were quality management, online office hours, quizzes midterm oral exams, video development, and student-student and instructor-student Q&A type between face-to-face and remote class. As combinations of factors, it was found that quality management×quiz×student Q&A and quality management×quiz×voting type had an effect on whether to run remote classes. Based on the results, we proposed to run and support remote classes in the post-COVID-19 era.

• Korean journal of communication and information
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• v.42
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• pp.79-106
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• 2008

Based on the third-person effect hypothesis, this study conducted a nation-wide online survey to assess how Korean voters perceived the mass media's effect on the candidates' image and voting behavior during the 17th presidential election. The research results showed that the voters tended to perceive that the mass media such as newspaper, television and the Internet had a greater effect on others than on themselves with regards to the formation of the three candidates' images. The third-person effect on the voting behavior was also revealed differently in terms of the medium according to age and political tendency of the voters. For instance, the younger and liberal voters were likely to see newspaper as having a greater influence on other voters' choice of candidate, while the older voters saw TV as having a greater effect on other voters. The conservative tendency did not affect the perception of the voters at all. Another noteworthy result was that personal characteristics of the candidates' images such as appearances and communication skills did not affect the voters' behaviors in the election process.

• Journal of Information Management
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• v.36 no.1
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• pp.57-75
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• 2005

The Industrial Metadata Registry(IMR) for standardizing industrial information metadata was implemented and four drafts of metadata sets were developed based on the ISO/IEC 11179. The IMR consists of four individual metadata registries characterized by subject category. Accordingly, the system includes the integrated administration module, and the divisions administration module. The users of the system are divided into committee members and general users. The system has been developed with Oracle 9i and Java JSP over Linux operating system. The system will support the procedure for data sharing and exchanging among users and organizations and improve the availability and manageability of data and provide the standardization of data across the industry.

• The Journal of the Korea Contents Association
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• v.19 no.4
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• pp.174-186
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• 2019

Twitter is very popluar with users who desire social interaction as it is a highly effective method of communicating compared to traditional communication platforms; and thus has garnered considerable interest from the academic community. This research reveals how election results can be predicted by the factors of total volume of messages, positive messages and negative messages tweeted about a candidate. Social matrix analysis revealed that the quantity of twitter messages was a strong predictor of election results in the 18th presidential election in Korea. In addition, more positive messages than negative messages about a candidate from twitter users recorded better results in the election. This research found that the total quantity of messages, positive messages, and negative messages as key factors for predicting election result. Future studies should investigate other SNS platforms to discover what is the most effective communication strategy on each platform.

• Journal of Korean Library and Information Science Society
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• v.46 no.3
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• pp.225-253
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• 2015

This study investigated the interactions between archives and users based on content analysis of posts of Facebook and Twitter operated by archival institutions. It focused on posts in official Facebooks and Twitters of the U.S. and the U.K. national archives. The posts included 66 in Facebook and 670 in Twitter of the U.S. national archives, as well as 73 in Facebook and 84 in Twitter of the U.K. national archive. The analysis showed that information sharing of in-house collections and online resources, as well as information dissemination of events were the most common interaction types of the posts. 1 and 1 communication or information gathering such as questionnaire or vote rarely happened. In addition, the extent of users' responses was great on posts regarding information sharing of in-house collections. Providing information about people or events with timely manners motivated interests and participations of users. It is necessary to consider various types of interactions that facilitate user engagement. It is also important to make efforts to provide timely records in connection with exiting web resources and a variety of social media provided by archival institutions.

• The Journal of the Korea Contents Association
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• v.15 no.6
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• pp.13-23
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• 2015

A study on the 'FUN' of TV reality audition programs. "Why are the audience so enthusiastic about the survival audition programs?" "What fun do the audition program audience have?" In order to find the answers for such questions, this study applied 'the 4-step fun evolving model' and thereby, categorized audience's fun-seeking behavioral modes, and therewith, examined how such fun-seeking behavioral modes would change by step over time. As a result, it was found that the audition program audience had faithfully followed the 4 fun types (watching, having, doing and becoming), and that their fun-seeking behavioral modes had changed by step over time in SBS "K-POP START" (Season 3) in 2013. Such findings suggest that the audition program fans accommodated 'the fun evolving model.' Their step of 'watching' evolved gradually into the step of 'having' both on-line and off-line (support of participants/malicious or good-will replies, participation in blogs/twitters, photo materials collection activities) and that of 'doing' (application for the jury group, organization of fan club, crazy fan activities, participation in phone voting, etc.), while increasing their fun.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.161-183
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• 2022

Opinion polls have become a powerful means for election campaigns and one of the most important subjects in the media in that they predict the actual election results and influence people's voting behavior. However, the more active the polls, the more often they fail to properly reflect the voters' minds in measuring the effectiveness of election campaigns, such as repeatedly conducting polls on the likelihood of winning or support rather than verifying the pledges and policies of candidates. Even if the poor predictions of the election results of the polls have undermined the authority of the press, people cannot easily let go of their interest in polls because there is no clear alternative to answer the instinctive question of which candidate will ultimately win. In this regard, we attempt to retrospectively grasp public opinion on the 20th presidential election by applying the 'YouTube Analysis' function of Sometrend, which provides an environment for discovering insights through online big data. Through this study, it is confirmed that a result close to the actual public opinion (or opinion poll results) can be easily derived with simple YouTube data results, and a high-performance public opinion prediction model can be built.

• Journal of the Korean Society for information Management
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• v.38 no.3
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• pp.23-39
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• 2021

This study aims to explore research trends in Blockchain studies in South Korea using dynamic topic modeling and network analysis. To achieve this goal, we conducted the university & institute collaboration network analysis, the keyword co-occurrence network analysis, and times series topic analysis using dynamic topic modeling. Through the university & institute collaboration network analysis, we found major universities such as Soongsil University, Soonchunhyang University, Korea University, Korea Advanced Institute of Science and Technology (KAIST) and major institutes such as Ministry of National Defense, Korea Railroad Research Institute, Samil PricewaterhouseCoopers, Electronics and Telecommunications Research Institute that led collaborative research. Next, through the analysis of the keyword co-occurrence network, we found major research keywords including virtual assets (Cryptocurrency, Bitcoin, Ethereum, Virtual currency), blockchain technology (Distributed ledger, Distributed ledger technology), finance (Smart contract), and information security (Security, privacy, Personal information). Smart contracts showed the highest scores in all network centrality measures showing its importance in the field. Finally, through the time series topic analysis, we identified five major topics including blockchain technology, blockchain ecosystem, blockchain application 1 (trade, online voting, real estate), blockchain application 2 (food, tourism, distribution, media), and blockchain application 3 (economy, finance). Changes of topics were also investigated by exploring proportions of representative keywords for each topic. The study is the first of its kind to attempt to conduct university & institute collaboration networks analysis and dynamic topic modeling-based times series topic analysis for exploring research trends in Blockchain studies in South Korea. Our results can be used by government agencies, universities, and research institutes to develop effective strategies of promoting university & institutes collaboration and interdisciplinary research in the field.