• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.199-219
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• 2018

With the everyday use of the Internet and the spread of various smart devices, users have been able to communicate in real time and the existing communication style has changed. Due to the change of the information subject by the Internet, data became more massive and caused the very large information called big data. These Big Data are seen as a new opportunity to understand social issues. In particular, text mining explores patterns using unstructured text data to find meaningful information. Since text data exists in various places such as newspaper, book, and web, the amount of data is very diverse and large, so it is suitable for understanding social reality. In recent years, there has been an increasing number of attempts to analyze texts from web such as SNS and blogs where the public can communicate freely. It is recognized as a useful method to grasp public opinion immediately so it can be used for political, social and cultural issue research. Text mining has received much attention in order to investigate the public's reputation for candidates, and to predict the voting rate instead of the polling. This is because many people question the credibility of the survey. Also, People tend to refuse or reveal their real intention when they are asked to respond to the poll. This study collected comments from the largest Internet portal site in Korea and conducted research on the 19th Korean presidential election in 2017. We collected 226,447 comments from April 29, 2017 to May 7, 2017, which includes the prohibition period of public opinion polls just prior to the presidential election day. We analyzed frequencies, associative emotional words, topic emotions, and candidate voting rates. By frequency analysis, we identified the words that are the most important issues per day. Particularly, according to the result of the presidential debate, it was seen that the candidate who became an issue was located at the top of the frequency analysis. By the analysis of associative emotional words, we were able to identify issues most relevant to each candidate. The topic emotion analysis was used to identify each candidate's topic and to express the emotions of the public on the topics. Finally, we estimated the voting rate by combining the volume of comments and sentiment score. By doing above, we explored the issues for each candidate and predicted the voting rate. The analysis showed that news comments is an effective tool for tracking the issue of presidential candidates and for predicting the voting rate. Particularly, this study showed issues per day and quantitative index for sentiment. Also it predicted voting rate for each candidate and precisely matched the ranking of the top five candidates. Each candidate will be able to objectively grasp public opinion and reflect it to the election strategy. Candidates can use positive issues more actively on election strategies, and try to correct negative issues. Particularly, candidates should be aware that they can get severe damage to their reputation if they face a moral problem. Voters can objectively look at issues and public opinion about each candidate and make more informed decisions when voting. If they refer to the results of this study before voting, they will be able to see the opinions of the public from the Big Data, and vote for a candidate with a more objective perspective. If the candidates have a campaign with reference to Big Data Analysis, the public will be more active on the web, recognizing that their wants are being reflected. The way of expressing their political views can be done in various web places. This can contribute to the act of political participation by the people.

• 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).

• 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 Environmental Policy
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• v.7 no.4
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• pp.105-134
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• 2008

Local opposition and protest constitute single greatest hurdle to the siting of locally unwanted land uses(LULUs), especially siting of high-level radioactive disposal not only throughout Korea but also throughout the industrialized world. It can be attributed mainly to the NIMBYism, equity problem, and lack of participation. These problems are arisen from rational planning process which emphasizes instrumental rationality. But planning is a value-laden political activity, in which substantive rationality is central. To achieve this goals, we need a sound planning process for siting LULUs, which should improve the ability of citizens to influence the decisions that affects them. By a sound planning process, we mean one that is open to citizen input and contains accurate and complete information. In other word, the public is also part of the goal setting process and, as the information and analyses developed by the planners are evaluated by the public, strategies for solutions can be developed through consensus-building. This method is called as a co-operative siting process, and must be structured in order to arrive at publicly acceptable decisions. The followings are decided by consensus-building method. 1. Negotiation will be held? 2. What is the benefits and risks of negotiation? 3. What are solutions when collisions between national interests and local ones come into? 4. What are the agendas? 5. What is the community' role in site selection? 6. Are there incentives to negotiation. 7. Who are the parties to the negotiation? 8. Who will represent the community? 9. What groundwork of negotiation is set up? 10. How do we assure that the community access to information and expert? 11. What happens if negotiation is failed? 12. Is it necessary to trust each other in negotiations? 13. Is a mediator needed in negotiations?

• Journal for History of Mathematics
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• v.22 no.2
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• pp.27-52
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• 2009

This article discusses the contributions of the leader Oswald Veblen, who was the president of AMS during 1923-1924. In 2006, Korea ranked 12th in SCIE publications in mathematics, more than doubling its publications in less than 10 years, a successful model for a country with relatively short history of modern mathematical research. Now there are 192 four-year universities in Korea. Some 42 of these universities have Ph.D. granting graduate programs in mathematics and/or mathematical education in Korea. Rapid growth is observed over a broad spectrum including a phenomenal performance surge in International Mathematical Olympiad. Western mathematics was first introduced in Korea in the 17th century, but real significant mathematical contributions by Korean mathematicians in modern mathematics were not much known yet to the world. Surprisingly there is no Korean mathematician who could be found in MaC Tutor History Birthplace Map. We are at the time, to have a clear vision and leadership for the 21st century. Even with the above achievement, Korean mathematical community has had obstacles in funding. Many people thinks that mathematical research can be done without funding rather unlike other science subjects, even though they agree fundamental mathematical research is very important. We found that the experience of early American mathematical community can help us to give a vision and role model for Korean mathematical community. When we read the AMS Notice article 'The Vision, Insight, and Influence of Oswald Veblen' by Steve Batterson, it answers many of our questions on the development of American mathematics in early 20th century. We would like to share the story and analyze its meaning for the development of Korean Mathematics of 21st century.

• 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 Southeast Asian review
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• v.27 no.2
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• pp.245-271
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• 2017

The purpose of this study is to examine and assess the major characteristics and changes of politics, economy, and diplomacy in Thailand in 2016. Specifically, it reviewed the New Constitution that was passed in 2016, the confrontation between different political forces and the trend of military regime around the New Constitution, and the political instability caused by the accession of the new king to the throne. This study also set out to figure out changes to the economy and foreign relations of the country, including its relations with South Korea, under the military regime and make predictions for the impact and future prospects of King Bhumibol Adulyadej's death on the politics and economy of the country. In 2016, the politics of Thailand took a step further toward the transfer of power to civil government and established a foundation for an authoritarian system. The draft of the New Constitution, which does not seem to be democratic, was approved by a referendum and enabled the military authorities to continue their political interventions, even after the general election. The New Constitution, in particular, reduces the power of political parties itself in addition to simply keeping the Thaksin's party in check; thus, anticipating ongoing conflicts between the military authorities and political parties. In this situation, the absence of King Bhumibol Adulyadej, who used to play a decisive role in promoting the political stability of the country, and the accession of the new king to the throne raise concerns about the acceleration of political instability, which has continued after the coup and influenced the diplomatic relations of the country. Today, Thailand is distancing itself from Western nations that do not recognize the current military regime including the U.S.A. and EU member states and instead maintains a rapidly friendly and close relation with China. In 2016, the economy of Thailand made a gradual recovery rather than high growth. The death of King Bhumibol Adulyadej has exerted limited direct economic impacts only on individual consumption and tourism and is not likely to cause a recession. An economic crisis will, however, be unavoidable if the political confrontations escalate before the general election to transfer power to the civil government.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.311-328
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• 2022

Because of the spread of smartphones due to the development of information and communication technology, online shopping mall services can be used on computers and mobile devices. As a result, the number of users using the online shopping mall service increases rapidly, and the types of products traded are also growing. Therefore, to maximize profits, companies need to provide information that may interest users. To this end, the recommendation system presents necessary information or products to the user based on the user's past behavioral data or behavioral purchase records. Representative overseas companies that currently provide recommendation services include Netflix, Amazon, and YouTube. These companies support users' purchase decisions by recommending products to users using ratings, purchase records, and clickstream data that users give to the items. In addition, users refer to the ratings left by other users about the product before buying a product. Most users tend to provide ratings only to products they are satisfied with, and the higher the rating, the higher the purchase intention. And recently, e-commerce sites have provided users with the ability to vote on whether product reviews are helpful. Through this, the user makes a purchase decision by referring to reviews and ratings of products judged to be beneficial. Therefore, in this study, the correlation between the product rating and the helpful information of the review is identified. The valuable data of the evaluation is reflected in the recommendation system to check the recommendation performance. In addition, we want to compare the results of skipping all the ratings in the traditional collaborative filtering technique with the recommended performance results that reflect only the 4 and 5 ratings. For this purpose, electronic product data collected from Amazon was used in this study, and the experimental results confirmed a correlation between ratings and review usefulness information. In addition, as a result of comparing the recommendation performance by reflecting all the ratings and only the 4 and 5 points in the recommendation system, the recommendation performance of remembering only the 4 and 5 points in the recommendation system was higher. In addition, as a result of reflecting review usefulness information in the recommendation system, it was confirmed that the more valuable the review, the higher the recommendation performance. Therefore, these experimental results are expected to improve the performance of personalized recommendation services in the future and provide implications for e-commerce sites.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.93-111
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• 2013

As Internet and information technology (IT) continues to develop and evolve, the issue of big data has emerged at the foreground of scholarly and industrial attention. Big data is generally defined as data that exceed the range that can be collected, stored, managed and analyzed by existing conventional information systems and it also refers to the new technologies designed to effectively extract values from such data. With the widespread dissemination of IT systems, continual efforts have been made in various fields of industry such as R&D, manufacturing, and finance to collect and analyze immense quantities of data in order to extract meaningful information and to use this information to solve various problems. Since IT has converged with various industries in many aspects, digital data are now being generated at a remarkably accelerating rate while developments in state-of-the-art technology have led to continual enhancements in system performance. The types of big data that are currently receiving the most attention include information available within companies, such as information on consumer characteristics, information on purchase records, logistics information and log information indicating the usage of products and services by consumers, as well as information accumulated outside companies, such as information on the web search traffic of online users, social network information, and patent information. Among these various types of big data, web searches performed by online users constitute one of the most effective and important sources of information for marketing purposes because consumers search for information on the internet in order to make efficient and rational choices. Recently, Google has provided public access to its information on the web search traffic of online users through a service named Google Trends. Research that uses this web search traffic information to analyze the information search behavior of online users is now receiving much attention in academia and in fields of industry. Studies using web search traffic information can be broadly classified into two fields. The first field consists of empirical demonstrations that show how web search information can be used to forecast social phenomena, the purchasing power of consumers, the outcomes of political elections, etc. The other field focuses on using web search traffic information to observe consumer behavior, identifying the attributes of a product that consumers regard as important or tracking changes on consumers' expectations, for example, but relatively less research has been completed in this field. In particular, to the extent of our knowledge, hardly any studies related to brands have yet attempted to use web search traffic information to analyze the factors that influence consumers' purchasing activities. This study aims to demonstrate that consumers' web search traffic information can be used to derive the relations among brands and the relations between an individual brand and product attributes. When consumers input their search words on the web, they may use a single keyword for the search, but they also often input multiple keywords to seek related information (this is referred to as simultaneous searching). A consumer performs a simultaneous search either to simultaneously compare two product brands to obtain information on their similarities and differences, or to acquire more in-depth information about a specific attribute in a specific brand. Web search traffic information shows that the quantity of simultaneous searches using certain keywords increases when the relation is closer in the consumer's mind and it will be possible to derive the relations between each of the keywords by collecting this relational data and subjecting it to network analysis. Accordingly, this study proposes a method of analyzing how brands are positioned by consumers and what relationships exist between product attributes and an individual brand, using simultaneous search traffic information. It also presents case studies demonstrating the actual application of this method, with a focus on tablets, belonging to innovative product groups.