• The Journal of the Korea Contents Association
• /
• v.12 no.8
• /
• pp.157-166
• /
• 2012

At the recent 19th General Election, Korean papers waged a surrogate war for the parties they share ideology with. All the conventional practices remained the same - the horse race-like presentations, furthering of confrontations, disregarding policy issues, allocating larger space for commentaries and negative issues, and etc. On top of these, papers began to focus on generational conflicts and individuals at the center of widespread attention and controversies, as a new trend. Photo images are largely used in the commentaries and articles dealing with confrontational or controversial situations. Of course, while the visual images seem to reinforce the emotional appeal of the messages papers try to get across, the potential problems need be noticed that could rise when irrelevant images are used.

• Informatization Policy
• /
• v.20 no.2
• /
• pp.3-19
• /
• 2013

Studies on the SNS political participation have covered issues of SNS effect on political participation, electoral campaigns, and the public sphere. Such issues as characteristics of SNS political participation, the characteristics of SNS users, SNS effect on the political participation, active SNS political participants, and the impact on young people's political participation, etc. have been studied in the area of political participation effect. On the election issues, SNS impact on election turnout, voting behavior, and the election results were main research topics. Finally, the research on the public sphere mainly discussed topics of quality of SNS information and social fragmentation phenomenon. What is commonly observed across all the three subjects is that the conflicting claims appear to almost all the topics. These contradictory findings are likely to occur because variables of real politics are not fully taken into account and research variables are not strictly manipulated. We can get more accurate research results in the study of SNS political participation when we conduct cross-national research reflecting the context of real politics and also designing independent variables more in detail and elaborately.

• The Korean Journal of Applied Statistics
• /
• v.27 no.4
• /
• pp.523-541
• /
• 2014

We apply a Bayesian estimation procedure to the analysis of roll call voting records on 2,389 bills processed during the 18th Korean National Assembly. The analysis of roll calls yields useful tools for to combining the measurement of legislative preference with the models of legislative behavior. The current Bayesian procedure is extremely exible, applicable to any legislative setting, irrespective of the extremism of the legislator's voting history or the number of roll calls available for analysis. It can be applied to any legislative settings, providing a useful solution to many statistical problems inherent in the analysis of roll call voting records. We rst estimate the ideal points of all members of the 18th National Assembly and their condence intervals. Subsequently, using the estimated ideal points, we examine the factional disparity within each major party using the estimated ideal points. Our results clearly suggest that there exists a meaningful ideological spectrum within each party. We also show how the Bayesian procedure can easily be extended to accommodate theoretically interesting theoretical models of legislative behavior. More specically, we demonstrate how the estimated posterior probabilities can be used for identifying pivotal legislators.

• Journal of Korean Institute of Industrial Engineers
• /
• v.40 no.1
• /
• pp.60-83
• /
• 2014

This paper aims to propose a research framework of analyzing voting activities of a national assembly on the basis of member-level voting similarity and provides a case study in the $18^{th}$ national assembly in South Korea. First, we propose a bill contentiousness measure that gives a higher score to bills for which ayes and noes are more diversified in both conservative and progressive parties. Based on the bill contentiousness measure, the top 5%, 10%, and 20% bills were identified and used for further analyses. Moreover, we propose a member-level voting similarity measure that compensates for the lower frequency of noes, and evaluate the pair-wise voting similarities for all lawmakers. Then, voting similarity differences to the affiliated/non-affiliated parties were analyzed for the members in the two major parties according to some internal/external key factors. Finally, similar voting groups were identified and their affiliations were investigated based on the multi-dimensional scaling (MDS) and network analysis techniques. A case study on the $18^{th}$ national assembly of South Korea showed that the cohesion of the members in the 'Hanara' party becomes higher than that of the 'Minju' party as the bill contentiousness increases, whereas the number of elected, local constituency versus proportional representation, and the competition intensity in a local constituency were found to be partially influential to the voting activities of lawmakers. In addition, MDS and network analysis showed that there is a distinctive difference between two parties when all bills are analyzed, whereas the diversity of parties increases in the same group as the bill contentiousness increases.

• Korean Journal of Legislative Studies
• /
• v.27 no.3
• /
• pp.35-68
• /
• 2021

In the German federal election in 2021, the Social Democrats returned to power by a narrow margin and the Green Party emerged as the biggest winner. The two political parties took the lead by proposing policies that met the expectations of the people in the policies of climate and environment, pandemic response and health, and labor and social security. The Merkel effect did not play a significant role in the election, and it is highly likely that it will lead to government policy after the formation of a coalition. While the class cleavage in voting behavior has weakened, the generational cleavage has grown relatively large. Older people showed more support for the two major parties, while younger people showed higher support for the Green Party and the FDP. If the generational cleavage continues, it can be linked to the growth of the Green Party and the FDP, the continued weakening of the two major parties and the emergence of other new parties. In addition, the regional cleavage between the former East and West Germany still remain, which will affect the direction of the AfD and the Left and combine with other political cleavages. The 2021 German federal election can be said to be an election that heralds the realignment of the political party system.

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