• Korean journal of communication and information
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• v.39
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• pp.284-323
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• 2007

This study aims to examine the relation between opinion perception and opinion expression by issue types by analyzing online poll results and respective bulletin boards. To find out how opinion poll results affect the public opinion perception cues and opinion expression through the internet, the study applied a method of content analysis to the online contents provided by Naver.com, one of the most popular portal sites in Korea. A total of four issue types, along with 2,250 messages were chosen for analysis. The study results revealed that internet users perceived opinion atmosphere through the poll results and expressed their opinions depending on the issue types. In case of an issue where majority views are manifested as online poll results, users tended to follow that majority views by retaining their initial opinion. Majority opinion by the poll results held a dominant position in bulletin board. The results partially support Noelle-Neuman(1994)'s spiral of silence theory in the context of computer-mediated communication contrary to the belief that anonymity in the cyberspace tends to encourage participation of minority opinion group. According to the findings, people when they perceive their opinion as that of minority are discouraged to express their views even when they are online.

• The Journal of the Convergence on Culture Technology
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• v.6 no.1
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• pp.111-120
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• 2020

As an application of big data and artificial intelligence techniques, this study proposes an atypical language-based sentimental opinion poll methodology, unlike conventional opinion poll methodology. An alternative method for the sentimental classification model based on existing statistical analysis was to collect real-time Twitter data related to parliamentary elections and perform empirical analyses on the Polarity and Intensity of public opinion using attribute-based sensitivity analysis. In order to classify the polarity of words used on individual SNS, the polarity of the new Twitter data was estimated using the learned Lasso and Ridge regression models while extracting independent variables that greatly affect the polarity variables. A social network analysis of the relationships of people with friends on SNS suggested a way to identify peer group sensitivity. Based on what voters expressed on social media, political opinion sensitivity analysis was used to predict party approval rating and measure the accuracy of the predictive model polarity analysis, confirming the applicability of the sensitivity analysis methodology in the political field.

• Journal of the Korean Data and Information Science Society
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• v.19 no.2
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• pp.431-441
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• 2008

A public opinion poll's importance is at this time increasing now. Especially, a news report with a fair and objective execution and investigative reporting Moral Code is very important. But a research on the basis of investigative reporting Moral Code is not yet carried out. In this paper, with the center of a public opinion poll involved in the 17th Presidential Election of Korea, investigative reporting Moral Code has been analyzed measurably how well observed in the Press. Furthermore, it has been compared with findings carried out in the year 2002. Finally, through comparing response rate with actual results acquired in a survey of public opinion, I proposed a response rate acquisition.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1800-1808
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• 2022

During the election period, many polling agencies survey and distribute the approval ratings for each candidate. In the past, public opinion was expressed through the Internet, mobile SNS, or community, although in the past, people had no choice but to survey the approval rating by relying on opinion polls. Therefore, if the public opinion expressed on the Internet is understood through natural language analysis, it is possible to determine the candidate's approval rate as accurately as the result of the opinion poll. Therefore, this paper proposes a method of inferring the approval rate of candidates during the election period by synthesizing the political comments of users through internet community posting data. In order to analyze the approval rate in the post, I would like to suggest a method for generating the model that has the highest correlation with the actual opinion poll by using the KoBert, KcBert, and KoELECTRA models.

• Proceedings of the KSR Conference
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• 2004.10a
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• pp.1677-1685
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• 2004

This is the analysis of the inquiry performed from April to May, 2004 for the effect of the high speed railways opened April 1st, 2004. This study tried to find the problem of KTX by an opinion poll and to improve the KTX service.

• The Korean Journal of Applied Statistics
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• v.20 no.1
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• pp.61-78
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• 2007

A method for poll analysis using information theory and data visualization is proposed in this paper. Questions of opinion poll consist of a target variable and many explanation variables. The type of explanation variables is either numerical or categorical. In this study, explanation variables of mixed types have been ranked according to the magnitude of their effect on target variable by using mutual information. Likewise, the order of explanation variables has been evaluated using data visualization. This is the first study to quantify the impact of specific explanation variable on the related target variable.

• Asian Journal for Public Opinion Research
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• v.5 no.1
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• pp.1-14
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• 2017

The Fukushima nuclear accident caused by an earthquake and a subsequent tsunami on March 11, 2011 has seriously impacted the environment surrounding the Fukushima Daiichi nuclear power plant. While all the residents near the plant were evacuated from the area deemed uninhabitable after the accident, residents of the neighboring area outside of the evacuation zone still seem to live in fear of invisible radiation. To understand Fukushima residents' thinking about the environmental risks that accompany a nuclear disaster, we utilize a poll of the residents of Fukushima conducted in 2013. Based on the survey data, we reveal factors that seem to strongly affect their knowledge and concerns about nuclear power plants. The results of the multivariate analysis show the importance of the following two factors: (1) confidence in mass media, and (2) trust in institutions in charge of administering the accident, especially the central government, the Nuclear and Industrial Safety Agency, and Tokyo Electric Power Company. We conclude that the more people trust mass media and particular institutions, the more likely it is that they are have an elevated sense of anxiety and fear of the presence of nuclear plants.

• Journal of Gifted/Talented Education
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• v.27 no.1
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• pp.97-118
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• 2017

This paper aims to provide reference model for directions and objectives of Software(SW) gifted education. In order to achieve the goals introduced above, we conducted the research in the following steps. First, we selected the concept of ICT-based creative talented person as a base model to establish the concept of SW gifted person. The selected base model composed three core competencies which were 'knowledge and technology competencies', 'synthesizing and creativity competencies', and 'personality competencies'. Second, we developed survey tools, like questionnaires, to investigate participant's recognition of SW gifted person. The survey tools composed three components 'computational thinking', 'entrepreneurship', and 'social responsibility'. Each of the components composed seven elements. Third, after selecting the opinion poll participants as an elementary school teacher, we surveyed opinion polling. By selecting an elementary school teacher as the opinion poll participants, we wanted to identify theirs ' opinions which are thought to be the starting point for gifted education. To survey we developed on-line survey system by using Google functions. Fourth, we analyzed the collected opinion data. To identify we summarized and synthesized participant's opinions that average values and agreement level by using frequency analysis. Also, in order to compare opinions that average values and agreement level based on whether or not participant's various experiences and competencies we computed t-value, F-value, and ${\chi}^2$ verification.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.161-183
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• 2022

Opinion polls have become a powerful means for election campaigns and one of the most important subjects in the media in that they predict the actual election results and influence people's voting behavior. However, the more active the polls, the more often they fail to properly reflect the voters' minds in measuring the effectiveness of election campaigns, such as repeatedly conducting polls on the likelihood of winning or support rather than verifying the pledges and policies of candidates. Even if the poor predictions of the election results of the polls have undermined the authority of the press, people cannot easily let go of their interest in polls because there is no clear alternative to answer the instinctive question of which candidate will ultimately win. In this regard, we attempt to retrospectively grasp public opinion on the 20th presidential election by applying the 'YouTube Analysis' function of Sometrend, which provides an environment for discovering insights through online big data. Through this study, it is confirmed that a result close to the actual public opinion (or opinion poll results) can be easily derived with simple YouTube data results, and a high-performance public opinion prediction model can be built.

• The Korean Journal of Applied Statistics
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• v.31 no.5
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• pp.655-665
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• 2018

Social network services (SNS) have become the most common tool for the communication of public and private opinions as well as public issues; consequently, one may form or drive public opinions to advocate by spreading positive content using SNS. Controversy for survey data based opinion poll accuracy continues in relation to response rate or sampling methodology. This study suggests complementary measures that additionally consider the sentiment analysis results of unstructured data on a social network by data crawling and sentiment dictionary adjustment process. The suggested method shows the improvement of prediction accuracy by decreasing error rates.