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.
The Journal of the Convergence on Culture Technology
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v.8
no.4
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pp.435-444
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2022
There are three focuses in the paper. Firstly, the study identified what channels were most viewed by YouTube users to watch the 'Daejang-dong scandal,' which was the most powerful agenda to influence the candidate preference among voters during the 20th presidential election. Secondly, the study analyzed whether the political tone of the first videos was in line with that of the subsequent videos. Finally, we compared the sentiment of comments on the first and subsequent videos. The results showed that TBS 'News Factory' and 'TV Chosun News' represented liberal and conservative factions, respectively. Secondly, the political tone of channels that were viewed subsequently was neutral, but the conservative channel users left more negative comments and that was significant statistically. In addition, about 80% of the conservative and liberal channel users shared the same political tendency with the channel they watched first, and more than 90% of the comments left at the subsequent videos in line with that of at the first news. Based on these results, the study concluded that the voters tended to seek political news that was similar with their political ideology, and it was considered a sort of echo chamber phenomenon on the YouTube. The study suggests that the performance of high-quality journalism by traditional news outlet might contribute to decrease the negative influence of political contents on YouTube users.
Communications for Statistical Applications and Methods
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v.26
no.3
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pp.261-272
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2019
In this paper, we propose a procedure to build a prediction interval of the sum of dependent binary random variables over a graph to account for the dependence among binary variables. Our main interest is to find a prediction interval of the weighted sum of dependent binary random variables indexed by a graph. This problem is motivated by the prediction problem of various elections including Korean National Assembly and US presidential election. Traditional and popular approaches to construct the prediction interval of the seats won by major parties are normal approximation by the CLT and Monte Carlo method by generating many independent Bernoulli random variables assuming that those binary random variables are independent and the success probabilities are known constants. However, in practice, the survey results (also the exit polls) on the election are random and hardly independent to each other. They are more often spatially correlated random variables. To take this into account, we suggest a spatial auto-regressive (AR) model for the surveyed success probabilities, and propose a residual based bootstrap procedure to construct the prediction interval of the sum of the binary outcomes. Finally, we apply the procedure to building the prediction intervals of the number of legislative seats won by each party from the exit poll data in the $19^{th}$ and $20^{th}$ Korea National Assembly elections.
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.
This study applies policy network theory to examine the main policy actors and their relations in the green growth policy making process. Also the development of and changes in South Korean government's green growth strategy are analyzed. The results demonstrate that the president and the presidential council were the key players to introduce and to push green growth policy in a short time. Policy influence and key roles were concentrated on them. The development of green growth policy were initiated from the president's change in perceived problems and preferences. He set green growth policy on the government's top priority. These changes lead to another changes in strategies, rules, norms and resources within the network. As a result, the president-led green growth policy established new laws, environmental regulations and governmental structures to facilitate the policy implementation. Green growth policy, however, was almost stopped after new presidential election in 2013. Because new government has a different national agenda, the previous governmental agenda lost its status as national priority. In addition, this study shows that government-led green growth in Korea has policy consistency problem after administration was changed by presidential election. Former president-led green growth policy making under the situation of the lack of policy participation from the private sector led to discontinuities in policy after a presidential term was over.
Journal of the Korean Data and Information Science Society
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v.25
no.1
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pp.53-64
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2014
One of the major problems to forecast election, especially based on survey, is nonresponse. We may have different forecasting results depend on method of imputation. Handling nonresponse is more important in a survey about sensitive subject, such as presidential election. In this research, we consider a model based method of nonresponse imputation. A model based imputation method should be constructed based on assumption of nonresponse mechanism and may produce different results according to the nonresponse mechanism. An assumption of the nonresponse mechanism is very important precondition to forecast the accurate results. However, there is no exact way to verify assumption of the nonresponse mechanism. In this paper, we compared the accuracy of prediction and assumption of nonresponse mechanism based on the result of presidential election exit poll. We consider maximum likelihood estimation method based on EM algorithm to handle assumption of the model of nonresponse. We also consider modified within precinct error which Bautista (2007) proposed to compare the predict result.
For Singapore, 2017 was an uneasy year. The presidential election was fraught with controversy since the revised Presidential Election Act allowed only one candidate to be eligible for the election. The bitter feud between Prime Minister Lee Hsien Loong and his siblings shocked many Singaporeans. Succession planning for the next top leadership is still veiled in obscurity. The anti-globalization trend and the increasing pressure to raise the tax have become major challenges for Singapore's economy to overcome. China's continuous diplomatic pressure has called into the question Singapore's pragmatic foreign policy. Although its relations with China were back to normal, Singapore, the ASEAN chair in 2018, is still facing intractable problems in safeguarding ASEAN centrality in the growing US-China rivalry. In the meantime, Singapore has pursued its diversity and equality, heading toward a more matured multi-racial and multi-cultural society in 2017. The first female president, Halimah Yacob, served as a symbolic epitome of Singapore's emphasis on diversity and harmony among different ethnic groups and minorities. This great milestone, however, has largely been questioned by Singaporeans, as it seemed to be a political gesture that only utilized Halimah's double minority in the level of ideologies. The election of the Malay president has led Singaporeans to think about the real equity and equality among minorities, while strongly motivated to move toward a more inclusive society. In 2018, Singaporean leaders will try to resolve many challenging problems by reaffirming leadership succession planning, which is expected to lead Singapore to pursue a more integrated society.
Choi, Ji Hyun;Cho, Dong Uk;Lee, Bum Joo;Kim, Chan Jung;Jeong, Yeon Man
The Journal of Korean Institute of Communications and Information Sciences
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v.41
no.5
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pp.602-609
/
2016
In a smart society, politicians analyze the big data of voters to build a favorable political positions. In other words, a variety of digital footprints uploaded in SNS or Internet are used to set the election strategies and political directions. In comparison, it is difficult for voters to extract intention information about how politicians are performing a political acts. Therefore, it is important that voters need to analyze what intention of politicians are like for two way interaction between voters and politicians. For this, in this paper, we want to do the identification by analyzing IT technologies to narrative styles of politicians who pursue relative advantages or gains compared to other competitors. The experiments will be carried out to identify about what relative advantages compared to other competitors by narrative styles of next presidential candidates who are expected to run into the next presidential election by analyzing the usual audio interviews.
We investigate and estimate the causal effect of the survey methods in telephone surveys for the 19th presidential election. For this causal study, we draw a causal graph that represents the causal relationship between variables. Then we decide which variables should be included in the model and which variables should not be. We explain why the research agency is a should-be variable and the response rate is a shouldnot-be variable. The effect of ARS can not be estimated due to data limitations. We have found that there is no significant difference in the effect of the proportion of cell phone survey if it is less than about 90 percent. But the support rate for Moon Jae-in gets higher if the survey is performed only by cell phones.
This study carried out a survey targeting sample of 609 audience panel voters of 15 regions including Seoul during the campaign period of Korean presidential election on December 19, 2012. It was analyzed that how the attitude to the candidate, the support to the policy and the voters'variables affected the vote-getting in the engagement attributes. The analysis shows that high participation of the engagement attributes does not always mean that the political candidate is satisfactory at the political campaign. The fact that high engagement attribute does not always affect the other attributes is interpreted that engagement attributes do not have correlation at the political campaign. And the candidate should approach the voters more carefully as there are differences among the engagement attributes in the attitude to the candidate and the support to the policy. In the engagement attributes, voters show little difference according to gender, region, income and marriage but show much difference according to age and education level. So it will be a principal index in the future political campaign.
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