• Nuclear industry
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• v.8 no.12 s.70
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• pp.22-25
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• 1988

현대사회에서는 대중의 견해를 묻기 위해 자주 여론조사를 실시한다. 그러나 여론조사는 주어지는 질문과 방법에 따라 나타나는 결과는 매우 상반되게 나타난다. 미국 에너지계발협의회(USCEA)의 Ann S. Bisconti 부이사장은 본고에서 여론조사의 위험성과 나타난 결과에 대해서 정확한 판단을 지적하고 있다.

• Nuclear industry
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• v.23 no.11 s.249
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• pp.9-20
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• 2003

이 연구는 원자력에 대한 국민들의 여론 형성 과정을 분석하고 효과적인 대중 커뮤니케이션 전략을 수립함으로써 궁극적으로 원자력의 사회적 수용성을 높이기 위한 목적으로 수행된 것이다. 주된 연구 내용은 (1) 일반 국민들의 매체 이용과 원자력에 대한 태도 형성 과정 분석 (2) 대중 매체의 원자력 관련 보도에 대한 내용 분석(content analysis) (3) 매체의 의제 설정(agenda-setting) 과정 분석을 위한 심층 인터뷰(FGI) (4) 효과적인 대중 커뮤니케이션 전략의 수립 등이다. 연구의 주요 내용을 3회에 걸쳐 연재한다.

• Informatization Policy
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• v.24 no.4
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• pp.3-16
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• 2017

With the development of social media services in the era of Web 2.0, the public opinion formation site has been partially shifted from the traditional mass media to social media. This phenomenon is continuing to expand, and public opinions on government polices created and shared on social media are attracting more attention. It is particularly important to grasp public opinions in policy formulation because setting up educational policies involves a variety of stakeholders and conflicts. The purpose of this study is to explore public opinions about education-related policies through an empirical analysis of social media documents on education policies using opinion mining techniques. For this purpose, we collected the education policy-related documents by keyword, which were produced by users through the social media service, tokenized and extracted sentimental qualities of the documents, and scored the qualities using sentiment dictionaries to find out public preferences for specific education policies. As a result, a lot of negative public opinions were found regarding the smart education policies that use the keywords of digital textbooks and e-learning; while the software education policies using coding education and computer thinking as the keywords had more positive opinions. In addition, the general policies having the keywords of free school terms and creative personality education showed more negative public opinions. As much as 20% of the documents were unable to extract sentiments from, signifying that there are still a certain share of blog posts or tweets that do not reflect the writers' opinions.

• The Journal of the Korea Contents Association
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• v.14 no.1
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• pp.139-149
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• 2014

This study attempts to explore the inter-media agenda setting effect between television and Twitter based on the framework of the two-step flow theory. Twitter's increasingly important role in political communication can be effectively addressed by examining the process by which Twitter users form their opinions on television debate program. Content analyses of Twitter discussions after television debate of the Korean presidential candidates provided interesting insights into how Twitter's opinion leaders reflect on the televised debates. The results show that Twitter mentions rather focus on personality traits of the candidates while television debates emphasize the candiates' policy issues. Specifically, Twitter users mainly concentrated on the political ideology and morality of the candidates. In sum, Twitter seems to have its own way of influencing the public opinion separately from the television.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.2
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• pp.335-343
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• 2014

It is more important to ensure the credibility of internet media which influence the public opinion. However, there are vague suspicions in public from the examples of manipulation of online reviews with anonymity. In this study, we explore the possibility of manipulating public opinion in online web sites. We investigate the characteristics of comments posted by users on web sites and compare each comments by using the cosine similarity function. Our result shows followings. First, we found a correlation between the similarities of comments and the article ranks in the web sites. Second, it is possible to identify abnormal user activities indicating excessive multiple posting, double posting and astroturf activities.

• 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 Internet Computing and Services
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• v.19 no.4
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• pp.53-63
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• 2018

The traditional mass media function of conveying information and forming public opinion has rapidly changed into an environment in which information and opinions are shared through social media with the development of ICT technology, and such social media further strengthens its influence. In other words, it has been confirmed that the influence of the public opinion through the production and sharing of public opinion on political, social and economic changes is increasing, and this change is already in use on the political campaign. In addition, efforts to grasp and reflect the opinions of the public by utilizing social media are being actively carried out not only in the political area but also in the public area. The purpose of this study is to explore the possibility of using social media based public opinion in educational policy. We collected media data, analyzed the main topic and probability of occurrence of each topic, and topic trends. As a result, we were able to catch the main interest of the public(the 'Domestic Computer Education Time' accounted for 43.99%, and 'Prime Project Selection' topics was 36.81% and 'Artificial Intelligence Program' topics was 7.94%). In addition, we could get a suggestion that flexible policies should be established according to the timing of the curriculum and the subject of the policy even if the category of the policy is same.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.3
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• pp.47-72
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• 2022

This study aims to understand the trends of subjects related to real estate policies and public's emotional opinion on the policies. Two keywords related to real estate policies such as "real estate policy" and "real estate measure" were used to collect tweets created from February 25, 2008 to August 31, 2021. A total of 91,740 tweets were collected and we applied sentiment analysis and dynamic topic modeling to the final preprocessed and categorized data of 18,925 tweets. Sentiment analysis and dynamic topic model analysis were conducted for a total of 18,925 posts after preprocessing data and categorizing them into supply, real estate tax, interest rate, and population variance. Keywords of each category are as follows: the supply categories (rental housing, greenbelt, newlyweds, homeless, supply, reconstruction, sale), real estate tax categories (comprehensive real estate tax, acquisition tax, holding tax, multiple homeowners, speculation), interest rate categories (interest rate), and population variance categories (Sejong, new city). The results of the sentiment analysis showed that one person posted on average one or two positive tweets whereas in the case of negative and neutral tweets, one person posted two or three. In addition, we found that part of people have both positive as well as negative and neutral opinions towards real estate policies. As the results of dynamic topic modeling analysis, negative reactions to real estate speculative forces and unearned income were identified as major negative topics and as for positive topics, expectation on increasing supply of housing and benefits for homeless people who purchase houses were identified. Unlike previous studies, which focused on changes and evaluations of specific real estate policies, this study has academic significance in that it collected posts from Twitter, one of the social media platforms, used emotional analysis, dynamic topic modeling analysis, and identified potential topics and trends of real estate policy over time. The results of the study can help create new policies that take public opinion on real estate policies into consideration.

• The Journal of Bigdata
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• v.8 no.1
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• pp.11-22
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• 2023

This research aimed to examine the public's perception of the "rate of sentence reduction for reasons of mental and physical weakness" and investigate if it aligns with the actual practice. Various sources, such as the Supreme Court's Courtnet search system, the number of mental evaluation requests, and the number of articles and comments related to "mental weakness" on Naver News were utilized for the analysis. The findings indicate that the public has a negative opinion on reducing sentences due to mental and physical weakness, and they are dissatisfied with the vagueness of the standards. However, this study also confirms that the court strictly applies the reduction of responsibility for individuals with mental disabilities specified in Article 10 of the Criminal Act based on the analysis of actual judgments and the number of requests for psychiatric evaluation. In other words, even though the recognition of perpetrators' mental disorders is declining, the public does not seem to recognize this trend. This creates a negative impact on the public's trust in state institutions. Therefore, law enforcement agencies, such as the police and prosecutors, need to enforce the law according to clear standards to gain public trust. The judiciary also needs to make a firm decision on commuting sentences for mentally and physically infirm individuals and inform the public of the outcomes of its application.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.4
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• pp.177-184
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• 2017

The abstract should concisely state what was done, how it was done, principal results, and their significance. It should be less than 300 words for all forms of publication. Recently social disasters have been occurring frequently in the increasing complicated social structure, and the scale of damage has also become larger. Accordingly, there is a need for a way to prevent further damage by rapidly responding to social disasters. Twitter is attracting attention as a countermeasure against disasters because of immediacy and expandability. Especially, collecting public opinion on Twitter can be used as a useful tool to prevent disasters by quickly responding. This study proposes a collecting method of Twitter public opinion through keyword analysis, issue topic tweet detection, and time trend analysis. Furthermore we also show the feasibility by selecting the case of humidifier disinfectant which is a social issue recently.