• Korean Journal of Legislative Studies
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• v.24 no.1
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• pp.171-202
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• 2018

Issue ownership concerns a party's issue handling reputation. When a party is perceived to have the best solution for an issue, voters identify the party as the owner of the issue. Extant literature of issue ownership voting shows that voters tend to vote for a party that they identify as the owner of an issue they concern most. That is, the effect of issue ownership on voting is conditioned by the perceived salience of the issue in question. This study investigates another condition of issue ownership voting: i.e. party behavior in election campaigns. It argues that the effect of issue ownership on voting is conditional: it depends on party behavior as well as issue salience. During the campaign in the 2016 legislative election, only the Democratic Party of Korea, the opposition party at that time, actively presented itself as the owner of economic issues. The analysis results of this study show that the identification of the Democratic Party as the economic issue owner affects voting for the party when a voter thinks the economy to be the most important issue. However, the identification of the other parties as the economic issue owner does not affect voting for them under the same condition. The results support the argument that party behavior as well as issue salience are conditions of issue ownership voting.

• The Southeast Asian review
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• v.28 no.3
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• pp.213-261
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• 2018

On May 9, 2018, regime change took place in Malaysia. It was the first regime change that took place in 61 years after independence in 1957. The regime change was an unexpected result not only in Malaysian experts but also in political circles. Moreover, the outcome of the election was more shocking because the opposition party was divided in this general election. The regime change in Malaysia was enough to attract worldwide attention because it meant the collapse of the oldest regime in the modern political system that exists, except North Korea and China. How could this have happened? In particular, how could the regime change, which had not been accomplished despite opposition parties' cooperation for almost 20 years, could be achieved with the divided opposition forces? What political implications does the 2018 general election result have for political change and democratization in Malaysia? How will the Malaysian politics be developed in the aftermath of the regime change? It is worth noting that during the process of finding answers, a series of general elections since the start of reformasi in 1998 tended to be likened to a series of "tsunami" in the Malaysian electoral history. This phenomenon of tsunami means that, even though very few predicted the possibility of regime change among academia, civil society and political circles, the regime change was not sudden. In other words, the regime in 2018 was the result of the desire and expectation of political change through a series of elections of Malaysian voters last 20 years. In this context, this study, in analyzing the results of the election in 2018, shows that the activation of electoral politics triggered by the reform movement in 1998, along with the specific situational factors in 2018, could lead to collapse of the ruling government for the first time since independence.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.4
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• pp.993-999
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• 2011

In WSN, at the initial stage, sensor nodes are randomly deployed over the region of interest, and self-configure the clustered networks by grouping a bunch of sensor nodes and selecting a cluster header among them. Specially, in WSN environment, in which the administrator's intervention is restricted, the self-configuration capability is essential to establish a power-conservative WSN which provides broad sensing coverage and communication coverage. In this paper, we propose a communication coverage-aware cluster head election algorithm for Herearchical WSNs which consists of communication coverage-aware of the Base station is the cluster head node is elected and a clustering.

• Journal of Korea Multimedia Society
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• v.9 no.12
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• pp.1542-1551
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• 2006

In the Grid Database, some replicas will have more requests from the clients than others. A fast consistency algorithm has been presented to satisfy the high demand nodes in a shorter period of time. But it has poor performance in multiple regions of high demand for forming the island of locally consistent replicas. Then, a leader election method is proposed, whereas it needs much additional cost for periodic leader election, information storage, and message passing, Also, false leader can be created. In this paper, we propose a tree-based algorithm for replica update propagation. Leader replicas with high demand are considered as the roots of trees which are interconnected. All the other replicas are sorted and considered as nodes of the trees. Once an update occurs at any replica, it need be transmitted to the leader replicas first. Every node that receives the update propagates it to its children in the tree. The update propagation is optimized by cost reduction for fixed propagation schedule. And it is also flexible for the dynamic model in which the demand conditions change with time.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.527-530
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• 2010

WSN is composed of a lot of small sensors with the limited hardware resources. In WSN, at the initial stage, sensor nodes are randomly deployed over the region of interest, and self-configure the clustered networks by grouping a bunch of sensor nodes and selecting a cluster header among them. Specially, in WSN environment, in which the administrator's intervention is restricted, the self-configuration capability is essential to establish a power-conservative WSN which provides broad sensing coverage and communication coverage. In this paper, we propose a communication coverage-aware cluster head election algorithm for Herearchical WSNs which consists of communication coverage-aware of the Base station is the cluster head node is elected and a clustering.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.928-931
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• 2014

The detection of human behavior from social media revolutionized health, business, criminal and political prediction. Significance of it, in incentive transformation of public opinion had already proven for developed countries in improving democratic process of elections. In $3^{rd}$ World countries, voters poll votes for personal interests being unaware of party manifesto or national interest. These issues can be addressed by social media, resulting as ongoing process of improvement for presently adopted electoral procedures. On the optimistic side, people of such countries applied social media to garner support and campaign for political parties in General Elections. Political leaders, parties, and people empowered themselves with social media, in disseminating party's agenda and advocacy of party's ideology on social media without much campaigning cost. To study effectiveness of social media inferred from individual's political behavior, large scale analysis, sentiment detection & tweet classification was done in order to classify, predict and forecast election results. The experimental results depicts that social media content can be used as an effective indicator for capturing political behaviors of different parties positive, negative and neutral behavior of the party followers as well as party campaign impact can be predicted from the analysis.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.445-454
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• 2021

Leader and leadership are one of the important aspects in the life of a country. This study aims to predict the intention of young voters to vote for state leader elections by expanding the theory of planned behavior to the Indonesian context. Apart from the importance of the presidential election, research rarely uses the theory of planned behavior, and to the best of researchers' knowledge, there are no studies that have applied the theory of planned behavior to predict the intention to vote for the president. Therefore, this study is an attempt to fill that gap. Two hundred questionnaires were distributed using non-probability purposive sampling. Data analysis was carried out using the structural equation modeling (SEM) approach. The results showed that attitude and behavior control were positively related to voters' intention to elect presidential candidates. Furthermore, information from social media also has a positive relationship with the attitude of choosing presidential candidates. However, the results also show that subjective norms do not have a significant relationship with voters' intention. This study contributes knowledge to researchers, practitioners, and policymakers about the factors that influence youth intention to vote in Indonesia, namely, attitudes, perceived behavior control, and information from social media.

• Analyses & Alternatives
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• v.6 no.1
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• pp.223-258
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• 2022

The 2018 local elections completely upended the composition of Busan's city council, with the council membership changing from being solidly and consistently conservative to being over 80% liberal. What explains this anomalous outcome? While existing literature suggests the outcome of the 2018 city council elections was the consequence of a combination of structural and strategic factors, such as the decline of regional voting, we argue that the individual-level evaluation of President Moon Jae-in is one of the primary factors driving this result. Although coattails effects are commonly considered in concurrent national legislative elections, the Presidentialized and nationalized politics of Korea makes it possible for Presidential elections to affect local elections as well. We assess our explanation through an analysis of repeated cross-sectional survey data collected just before the 2018 local elections. The results of the analysis show that support for the Democratic Party is very strongly predicted by individual-level evaluation of President Moon. When considered in the context of the timing of presidential and local elections, the results suggest that Presidential coattail effects are capable of destabilizing established political patterns, such as regional voting, if perhaps only in a sporadic and idiosyncratic fashion, depending on whether or not local elections are held early on in a President's term.

• 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.

• Korean journal of communication and information
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• v.45
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• pp.220-254
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• 2009

Presidential TV debates serve as an important instrument for the general viewers to evaluate the candidates’ character, to examine their policy, and finally to make an important political decisions to cast ballots. Every words candidates utter in the course of entire election campaign exert influence of a certain significance by delivering their ideas and by creating clashes with their respective opponents. This study focuses on the conceptual venue, coined as ‘stasis’ by ancient rhetoricians, in which the clashes take place, and examines the words selection made by each candidates, the manners in which they form stasis, call for evidence, educate the public, and finally create a legitimate form of political argumentation. The study applied computer based content analysis using KrKwic and UCINET software to analyze semantic networks among the candidates. The results showed three major candidates, namely Lee Myung Bak, Jung Dong Young, and Lee Hoi Chang, displayed separate patterns in their use of language, by selecting the words that are often neglected by their opponents. Apparently, the absence of stasis and the lack of speaking mutual language significantly undermined the effects of debates. Central questions regarding issues of North Korea failed to meet basic requirements, and the respondents failed to engage in effective argumentation process.