• Korean Security Journal
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• no.22
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• pp.169-196
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• 2010

Although more priority is given to politicians from the aspect that they represent people and decide the future of country, the current situation is that politicians are not free from terrorism because of insufficient guard-concerned law, negative social recognition and increased crime and terrorism. The measure for politician terrorism shall be handled from the aspect of national security rather than public peace. For the purpose, basic legal foundation shall be prepared and specialized guard technique considering specialty of politician shall be established. Basic solution shall be established by reinforcing law against politician terrorism and establishing new law from the national viewpoint. The guard for politician has two faces that both of safety of guard target and voting intention of voter shall be met at the same time. Although special guard technique is required for guarding politician, current situation is that it is not researched professionally. In relation to the measure to develop the system of protection for politician, First, the study suggested legal foundation for politician guard. Although the 17th National Assembly proposed revised legal plan to protect politician from terrorism, it is suspended, expired and abolished now. The legal plan presented by members of the National Assembly was simply restricted to the scope of public guard. The study divided establishment of legal foundation into two things. The first one is the dispatch type of effective public guard and the second one is the transfer to private guard. Second, the study suggested environmental development method of politician guard. in the environment of politician guard, the study suggested improvement and development method by analyzing social recognition, politician's mind and voter's mind psychologically. After the beginning of human society, if human race is continued, political activity won't disappear. It is obvious that the safety of political leader is very important issue for human race because he plays the role to decide the future of human. In the future, more specialized, effective law shall be prepared and deeper study of scholar shall be performed.

• The Journal of Society for e-Business Studies
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• v.17 no.4
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• pp.69-93
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• 2012

Various influence-related relationships in Social Network Services (SNS) among users, posts, and user-and-post, can be expressed using links. The current research evaluates the influence of specific users or posts by analyzing the link structure of relevant social network graphs to identify influential users. We applied the concept of mutual interactions proposed for ranking semantic web resources, rather than the voting notion of Page Rank or HITS, to blogosphere, one of the early SNS. Through many experiments with network models, where the performance and validity of each alternative approach can be analyzed, we showed the applicability and strengths of our approach. The weight tuning processes for the links of these network models enabled us to control the experiment errors form the link weight differences and compare the implementation easiness of alternatives. An additional example of how to enter the content scores of commercial or spam posts into the graph-based method is suggested on a small network model as well. This research, as a starting point of the study on identifying influential users in SNS, is distinctive from the previous researches in the following points. First, various influence-related properties that are deemed important but are disregarded, such as scraping, commenting, subscribing to RSS feeds, and trusting friends, can be considered simultaneously. Second, the framework reflects the general phenomenon where objects interacting with more influential objects increase their influence. Third, regarding the extent to which a bloggers causes other bloggers to act after him or her as the most important factor of influence, we treated sequential referencing relationships with a viewpoint from that of PageRank or HITS (Hypertext Induced Topic Selection).

• The Korean Journal of Air & Space Law and Policy
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• v.31 no.2
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• pp.237-269
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• 2016

Asia-Pacific Space Cooperation Organization (APSCO) is the only intergovernmental space cooperation organization in Asia. Since its establishment to date, eight countries have signed the convention and become member states. South Korea participated actively in the preparatory phase of creating the organization, and one conference organized by AP-MCSTA which is the predecessor of APSCO was held in South Korea. However, after the APSCO Convention was opened for signature in 2005 to date, South Korea does not ratify the Convention and become a member. The rapid development of space commercialization and privatization, as well as the fastest growing commercial space market in Asia, provides opportunities for Asian countries to cooperate with each other in relevant space fields. And to participate in the existing cooperation framework (e.g., the APSCO) by the Asian space countries (e.g., South Korea) could be a proper choice. Even if the essential cooperation in particular space fields is challenging, joint space programs among different Asian countries for dealing with the common events can be initiated at the first steps. Since APSCO has learned the successful legal arrangements from ESA, the legal measures established by its Convention are believed to be qualified to ensure the achievement of benefits of different member states. For example, the regulation of the "fair return" principle confirms that the return of interests from the relevant programs is in proportion to the member's investment in the programs. Moreover, the distinguish of basic and optional activities intends to authorize the freedom of the members to choose programs to participate. And for the voting procedure, the acceptance of the "consensus" by the Council is in favor of protecting the member's interest when making decisions. However, political factors that are potential to block the participation of South Korea in APSCO are difficult to be ignored. A recent event is an announcement of deploying THAAD by South Korea, which causes tension between South Korea and China. The cooperation between these two states in space activities will be influenced. A long-standing barrier is that China acts as a non-member of the main international export control mechanism, i.e., the MTCR. The U.S takes this fact as the main reason to prevent South Korea to cooperate with China in developing space programs. Although the political factors that will block the participation of South Korea in APSCO are not easy to removed shortly, legal measures can be taken to reduce the political influence. More specifically, APSCO is recommended to ensure the achievement of commercial interests of different cooperation programs by regulating precisely the implementation of the "fair return" principle. Furthermore, APSCO is also suggested to contribute to managing the common regional events by sharing satellite data. And it is anticipated that these measures can effectively response the requirements of the rapid development of space commercialization and the increasing common needs of Asia, thereby to provide a platform for the further cooperation. In addition, in order to directly reduce the political influence, two legal measures are necessary to be taken: Firstly, to clarify the rights and responsibilities of the host state (i.e., China) as providing assistance, coordination and services to the management of the Organization to release the worries of the other member states that the host state will control the Organization's activities. And secondly, to illustrate that the cooperation in APSCO is for the non-military purpose (a narrow sense of "peaceful purpose") to reduce the political concerns. Regional cooperation in Asia regarding space affairs is considered to be a general trend in the future, so if the participation of South Korea in APSCO can be finally proved to be feasible, there will be an opportunity to discuss the creation of a comprehensive institutionalized framework for space cooperation in Asia.

• Journal of the Korean Society for Marine Environment & Energy
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• v.13 no.3
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• pp.135-150
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• 2010

At the Intergovernmental Meeting held in 1972, the London Convention was adopted to prevent marine pollution from dumping of wastes and other matter. After that, at the special meeting held at the Headquarters of the International Maritime Organization in 1996, the London Convention was revised to consider advances in technology of treatment and disposal of wastes and to reflect changes in understanding of marine environment and then the London Protocol was concluded. The London Protocol states more concrete management system for ocean dumping than the London Convention and also provides that the Meeting of Contracting Parties shall establish those procedures and mechanisms necessary to assess and promote compliance with the Protocol. With the London Protocol in force since 24 March 2006, the Meeting of Contracting Parties adopted the 'Compliance Procedures and Mechanisms (CPM) pursuant to Article 11 of the 1996 Protocol to the London Convention 1972' and established the Compliance Group in 2007. According to the CPM, members of the Compliance Group shall be nominated by Contracting Parties, based on equitable and balanced geographic representation of the five Regional Groups of the United Nations, and elected by the Meeting of Contracting Parties. In 2009, the Republic of Korea nominated a member of the Compliance Group to be subsequently elected by the Meeting of Contracting Parties with the approval of other states in Asia Group. Through the United Nations Regional Group System based on geographical identity or political affinity, Contracting Parties to the London Protocol are expected to form a voting bloc or to exchange information in meetings on the London Protocol. In this sense, it is noteworthy that the London Protocol introduced marine environmental management system for comprehensive prohibition of ocean dumping with exception of the so-called 'reverse-list' which had been earlier adopted by the 'Convention for the Protection of the Marine Environment of the North-East Atlantic, 1992 (OSPAR)' whose contracting parties belonged to Western European and Other States Group. In recent years, the jurisdiction of London Protocol has been extended to protect and preserve the marine environment from all sources of pollution. This will make the United Nations Regional Group System play more important roles in the activities associated with the London Protocol. For this reason, this article has considered characteristics of the United Nations Regional Group System and has analyzed influences of this Regional Group System in meetings on the London Protocol. This could provide preliminary information for the Republic of Korea to give due consideration to the United Nations Regional Group System on the activities associated with the London Protocol.

• 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.

• The Critical Review of Religion and Culture
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• no.29
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• pp.134-167
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• 2016

This paper aims at exploring the characteristics and meanings of religious freedom controversy surrounding religious education, with special reference to proselytism, in protestant mission school in recent Korea. Most of protestant mission schools have been providing students compulsory religion class and chapel service in the name of religious education. According to the school authorities, religious education should be provided for the realization of founding philosophy, and they say that mission school has the right to religious education. On the contrary, many non-christian students argue that their religious liberty is seriously violated by required religious education especially compulsory chapel worship. So serious conflicts broke between mission school authorities and students. Supreme Court decided that Soongsil University has the right to maintain compulsory chapel service, ruling that Daegwang High School should not maintain required chapel worship. It seems that Supreme Court gave different decisions to high school and university respectively, considering the differences between high school and university in application for admission to a school, students' critical consciousness, school's autonomous rights, etc. However, these precedents are being challenged by many peoples and groups. There are three agents which are involved in religious freedom controversy in mission school. The first are mission school authorities supported by religious groups, the second government supported by political parties, and the third mission school students guided by NGO. Among them protestant groups are playing the major role in making religious freedom problems in mission school. Protestant groups try to convert mission school students to protestantism by compulsory chapel service and religion class. Such a protestant proselytism becomes a cause of oppressing students' human rights and religious liberty. In this situation government has a responsibility to protect the students' rights to religious freedom. But government seldom impose sanctions on the protestant mission schools' compulsory programs. The reason why government does not restrict mission school's unlawful religious education is because protestant groups have strong influence in voting. Eventually civil movements organizations involved in religious freedom controversy for the sake of students's human rights. In conclusion, the assailment is protestant proselytism, the accessory is government, the victim is students in the religious education in mission school in recent Korea.

• Analyses & Alternatives
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• v.6 no.2
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• pp.79-115
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• 2022

This study aims to account for electoral choice in the 2020 presidential election by focusing on social identity which forms the basis for core partisan groups. Two views compete to explain the origins of polarization, policy versus party. One emphasizes policy as more influential in choosing presidential candidates. This follows the tradition of retrospective voting theory in which voters' choice rely on government performance. Incumbent president whose performance proves well are rewarded to be reelected. Policy performance is based on measures around distinctive preferences for government spending. Republican Individuals prefer individual responsibility to government support, while Democratic counterparts support government support. Another perspective put an emphasis on the role partisanship which favors in-party members and disfavors partisan out-groups. Interparty animosity plays the key role in determining electoral behavior. This study relies on the Views of the Electorate Research (VOTER) Survey which provides a panel data of several waves from 2011 to 2020. A comparative evaluation of two views highlights three findings. First, policy matters. Policy preferences of voters are the primary drives of political behavior. Electoral outcomes in 2020 turned out to be the results of policy considerations of voters. 53.7 percent of voters tilted toward individual responsibility voted for Trump, whereas 70.4 percent of those favorable views of government support than individual responsibility voted for Biden. Thus effects of policy correspond to a positive difference of 26.4 percent points. Second, partisanship effects are of similar extent in influencing electoral choice of candidates: Democrats are less likely to vote for Trump by 42.4 percent points, while Republicans are less likely to vote for Biden by 48.7 percent points. Third, animosity of Republicans toward Democrat core groups creates 26.5 percent points of favoring Trump over Biden. Democrat animosity toward Republican core groups creates a positive difference of 13.7 percent points of favoring Biden.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.141-156
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• 2013

Social media is a representative form of the Web 2.0 that shapes the change of a user's information behavior by allowing users to produce their own contents without any expert skills. In particular, as a new communication medium, it has a profound impact on the social change by enabling users to communicate with the masses and acquaintances their opinions and thoughts. Social media data plays a significant role in an emerging Big Data arena. A variety of research areas such as social network analysis, opinion mining, and so on, therefore, have paid attention to discover meaningful information from vast amounts of data buried in social media. Social media has recently become main foci to the field of Information Retrieval and Text Mining because not only it produces massive unstructured textual data in real-time but also it serves as an influential channel for opinion leading. But most of the previous studies have adopted broad-brush and limited approaches. These approaches have made it difficult to find and analyze new information. To overcome these limitations, we developed a real-time Twitter trend mining system to capture the trend in real-time processing big stream datasets of Twitter. The system offers the functions of term co-occurrence retrieval, visualization of Twitter users by query, similarity calculation between two users, topic modeling to keep track of changes of topical trend, and mention-based user network analysis. In addition, we conducted a case study on the 2012 Korean presidential election. We collected 1,737,969 tweets which contain candidates' name and election on Twitter in Korea (http://www.twitter.com/) for one month in 2012 (October 1 to October 31). The case study shows that the system provides useful information and detects the trend of society effectively. The system also retrieves the list of terms co-occurred by given query terms. We compare the results of term co-occurrence retrieval by giving influential candidates' name, 'Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn' as query terms. General terms which are related to presidential election such as 'Presidential Election', 'Proclamation in Support', Public opinion poll' appear frequently. Also the results show specific terms that differentiate each candidate's feature such as 'Park Jung Hee' and 'Yuk Young Su' from the query 'Guen Hae Park', 'a single candidacy agreement' and 'Time of voting extension' from the query 'Jae In Moon' and 'a single candidacy agreement' and 'down contract' from the query 'Chul Su Ahn'. Our system not only extracts 10 topics along with related terms but also shows topics' dynamic changes over time by employing the multinomial Latent Dirichlet Allocation technique. Each topic can show one of two types of patterns-Rising tendency and Falling tendencydepending on the change of the probability distribution. To determine the relationship between topic trends in Twitter and social issues in the real world, we compare topic trends with related news articles. We are able to identify that Twitter can track the issue faster than the other media, newspapers. The user network in Twitter is different from those of other social media because of distinctive characteristics of making relationships in Twitter. Twitter users can make their relationships by exchanging mentions. We visualize and analyze mention based networks of 136,754 users. We put three candidates' name as query terms-Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn'. The results show that Twitter users mention all candidates' name regardless of their political tendencies. This case study discloses that Twitter could be an effective tool to detect and predict dynamic changes of social issues, and mention-based user networks could show different aspects of user behavior as a unique network that is uniquely found in Twitter.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.83-102
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• 2021

The government recently announced various policies for developing big-data and artificial intelligence fields to provide a great opportunity to the public with respect to disclosure of high-quality data within public institutions. KSURE(Korea Trade Insurance Corporation) is a major public institution for financial policy in Korea, and thus the company is strongly committed to backing export companies with various systems. Nevertheless, there are still fewer cases of realized business model based on big-data analyses. In this situation, this paper aims to develop a new business model which can be applied to an ex-ante prediction for the likelihood of the insurance accident of credit guarantee. We utilize internal data from KSURE which supports export companies in Korea and apply machine learning models. Then, we conduct performance comparison among the predictive models including Logistic Regression, Random Forest, XGBoost, LightGBM, and DNN(Deep Neural Network). For decades, many researchers have tried to find better models which can help to predict bankruptcy since the ex-ante prediction is crucial for corporate managers, investors, creditors, and other stakeholders. The development of the prediction for financial distress or bankruptcy was originated from Smith(1930), Fitzpatrick(1932), or Merwin(1942). One of the most famous models is the Altman's Z-score model(Altman, 1968) which was based on the multiple discriminant analysis. This model is widely used in both research and practice by this time. The author suggests the score model that utilizes five key financial ratios to predict the probability of bankruptcy in the next two years. Ohlson(1980) introduces logit model to complement some limitations of previous models. Furthermore, Elmer and Borowski(1988) develop and examine a rule-based, automated system which conducts the financial analysis of savings and loans. Since the 1980s, researchers in Korea have started to examine analyses on the prediction of financial distress or bankruptcy. Kim(1987) analyzes financial ratios and develops the prediction model. Also, Han et al.(1995, 1996, 1997, 2003, 2005, 2006) construct the prediction model using various techniques including artificial neural network. Yang(1996) introduces multiple discriminant analysis and logit model. Besides, Kim and Kim(2001) utilize artificial neural network techniques for ex-ante prediction of insolvent enterprises. After that, many scholars have been trying to predict financial distress or bankruptcy more precisely based on diverse models such as Random Forest or SVM. One major distinction of our research from the previous research is that we focus on examining the predicted probability of default for each sample case, not only on investigating the classification accuracy of each model for the entire sample. Most predictive models in this paper show that the level of the accuracy of classification is about 70% based on the entire sample. To be specific, LightGBM model shows the highest accuracy of 71.1% and Logit model indicates the lowest accuracy of 69%. However, we confirm that there are open to multiple interpretations. In the context of the business, we have to put more emphasis on efforts to minimize type 2 error which causes more harmful operating losses for the guaranty company. Thus, we also compare the classification accuracy by splitting predicted probability of the default into ten equal intervals. When we examine the classification accuracy for each interval, Logit model has the highest accuracy of 100% for 0~10% of the predicted probability of the default, however, Logit model has a relatively lower accuracy of 61.5% for 90~100% of the predicted probability of the default. On the other hand, Random Forest, XGBoost, LightGBM, and DNN indicate more desirable results since they indicate a higher level of accuracy for both 0~10% and 90~100% of the predicted probability of the default but have a lower level of accuracy around 50% of the predicted probability of the default. When it comes to the distribution of samples for each predicted probability of the default, both LightGBM and XGBoost models have a relatively large number of samples for both 0~10% and 90~100% of the predicted probability of the default. Although Random Forest model has an advantage with regard to the perspective of classification accuracy with small number of cases, LightGBM or XGBoost could become a more desirable model since they classify large number of cases into the two extreme intervals of the predicted probability of the default, even allowing for their relatively low classification accuracy. Considering the importance of type 2 error and total prediction accuracy, XGBoost and DNN show superior performance. Next, Random Forest and LightGBM show good results, but logistic regression shows the worst performance. However, each predictive model has a comparative advantage in terms of various evaluation standards. For instance, Random Forest model shows almost 100% accuracy for samples which are expected to have a high level of the probability of default. Collectively, we can construct more comprehensive ensemble models which contain multiple classification machine learning models and conduct majority voting for maximizing its overall performance.