• Asian Journal for Public Opinion Research
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• v.11 no.4
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• pp.327-357
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• 2023

Adopting the Tools of Liberalism and Clash of Civilizations theories of international relations, this study examines the perceptions of 25,406 Arabs in 11 Arab countries as expressed in an Arab Barometer survey exploring their perceptions of violence against the United States (US), American citizens as "good," President Donald Trump's foreign policy in the Middle East, increasing economic relations with the US, and welcoming American foreign aid. As aspects of the Clash of Civilizations theory, this study examines religiosity, religious ritual practices, and political Islam and, as aspects of liberalism, this study explores the roles of online media as well as perceptions about US foreign aid in the prediction of the criterion variables. The findings suggest that religious indicators, and aspects of the Clash of Civilizations generally, were negative predictors of the perceptions, while social media and motivations for US foreign aid as aspects of liberalism, positively predicted the perceptions. The study discusses the results in relation to implications for policy makers.

• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.149-156
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• 2021

Text mining is one of the useful tools to discover public opinion and perception regarding political issues from big data. It is very common that users of social media express their opinion with newly-coined words such as slang and emoji. However, those new words are not effectively captured by traditional text mining methods that process text data using a language dictionary. In this study, we propose effective methods to extract newly-coined words that connote the political stance and opinion of users. With various text mining techniques, I attempt to discover the context and the political meaning of the new words.

• Journal of information and communication convergence engineering
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• v.15 no.3
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• pp.170-174
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• 2017

Nowadays, people share and discuss scientific papers on social media such as the Web 2.0, big data, online forums, blogs, Twitter, Facebook and scholar community, etc. In addition to a variety of metrics such as numbers of citation, download, recommendation, etc., paper review text is also one of the effective resources for the study of scientific impact. The social media tools improve the research process: recording a series online scholarly behaviors. This paper aims to research the huge amount of paper reviews which have generated in the social media platforms to explore the implicit information about research papers. We implemented and shown the result of text mining on review texts using R language. And we found that Zika virus was the research hotspot and association research methods were widely used in 2016. We also mined the news review about one paper and derived the public opinion.

• Journal of Korean Academy of Nursing
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• v.49 no.6
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• pp.736-747
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• 2019

Purpose: This study aimed to explore public opinion on workplace bullying in the nursing field, by analyzing the keywords and topics of online news comments. Methods: This was a text-mining study that collected, processed, and analyzed text data. A total of 89,951 comments on 650 online news articles, reported between January 1, 2013 and July 31, 2018, were collected via web crawling. The collected unstructured text data were preprocessed and keyword analysis and topic modeling were performed using R programming. Results: The 10 most important keywords were "work" (37121.7), "hospital" (25286.0), "patients" (24600.8), "woman" (24015.6), "physician" (20840.6), "trouble" (18539.4), "time" (17896.3), "money" (16379.9), "new nurses" (14056.8), and "salary" (13084.1). The 22,572 preprocessed key words were categorized into four topics: "poor working environment", "culture among women", "unfair oppression", and "society-level solutions". Conclusion: Public interest in workplace bullying among nurses has continued to increase. The public agreed that negative work environment and nursing shortage could cause workplace bullying. They also considered nurse bullying as a problem that should be resolved at a societal level. It is necessary to conduct further research through gender discrimination perspectives on nurse workplace bullying and the social value of nursing work.

• Korean journal of communication and information
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• v.23
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• pp.189-221
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• 2003

This study compares the influence of perceived public opinion on Internet users' willingness to expression in real space with in cyber space. In real space, people who perceive their opinions as minority opinion are reluctant to express theirs publicly because of fear of isolation. But cyber space is the anonymous world. So we can expect that people express their opinions freely without the fear of isolation in this space. This study's results provide the support for our expectation. In cyber space, the minority perception group has as the high willingness to expression of their opinion about the abrogation of the Korean Family Rights Raw as the majority perception group. Both of in cyber space and in real space, it is the perception failure group that makes discrepancy in the willingness to expression. This group has the lowest willingness to expression in both space. However, the other predictors of willingness to expression in cyber space are similar to those in real space. Issue salience, Communication apprehension, and Age are the very significant predictors of willingness to expression in both spaces. Sex and ideology are significant predictors in real space, while the frequency of online conversation is the significant predictor in cyber space.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.394-395
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• 2023

"이성적이며 이상적인 합리적 인간"을 가정하는 기존 경제학의 이론이 항상 실제 상황과 일치하지는 않는 것으로 알려져 있다. 이의 대안으로 나온 행동경제학은, 인간의 경제적 의사결정에 심리, 인지, 감정, 사회문화적 배경 등이 영향을 미친다고 본다. 본 연구에서는 행동경제학에 의거하여, 개인의 감정과 경험이 경제적 의사결정에 영향을 미치는지 여부를 빅데이터 모델을 활용하여 분석하였다. SNS 여론으로는 Reddit, 주가지수로는 S&P 500 을 선정하였다. 수집한 텍스트 데이터를 전처리와 감정분석을 통해 독립변수 값으로 사용했고, 주가지수 등락의 방향성을 종속변수로 사용하여 로지스틱 모형을 구성했다. 모델을 활용하여 분석한 결과 Public sentiment 와 Market sentiment 간 양의 상관관계를 확인할 수 있었다. 또한, lag 를 설정하는 모델이 정확도가 더욱 높음을 확인해, 기존 경제학의 EMH 와 대립되는 바를 확인할 수 있었다. 하지만 최적의 lag 산정을 위해, 더 광범위한 데이터를 바탕으로 한 후속연구가 필요하다.

• Asian Journal for Public Opinion Research
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• v.10 no.4
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• pp.316-339
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• 2022

The effects of the COVID-19 pandemic across various sectors are far-reaching, and the education sector is not an exemption. Approved and recognized vaccines are clinically proven to provide protection and have been considered one of the primary mitigations against the virus. Knowledge, attitude, and related practices (henceforth KAP) toward the virus is widely considered to be an essential cognitive key in public health for health intervention, prevention, and promotion. Previous studies revealed a positive correlation between knowledge and attitude. This study investigated the KAP and their relationship among the 857 college students in one state college in the Philippines using an online survey. Using descriptive statistics, the findings showed that the majority of the respondents have been fully vaccinated against COVID-19. Respondents were shown to be knowledgeable about COVID-19, specifically about its transmission, clinical symptoms, treatment, risk groups, isolation, prevention, and control. Positive attitudes toward individual and governmental mitigation and control of the virus were shown. Their scores on practices revealed that they always exhibit protective and preventive behavioral practices. Pearson correlation revealed a weak significant relationship between knowledge and practice, and a fair significant relationship between attitude and practice. No significant relationship is found between knowledge and attitude. This study hopes to find its place in the literature worthy of consideration as empirical support toward understanding a specific group's perceptive risk and preventive behavior toward the virus, policy making, and health intervention and promotion.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.45-54
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• 2022

This study examines the actual operation and performance of the public participation platform by analyzing various public participation processes from 2018 to 2021, when 'Gwanghwamun 1st Street', a representative public participation platform operated by the Ministry of Public Administration and Security, was launched. Through this, the influencing factors that were able to successfully induce the process of policyization through public participation were derived as follows. First, online participation channels were diversified to encourage public participation. Second, it is also important that the public opinion contest and compensation for public review were implemented to encourage and expand public participation. Third, the participation of experts was encouraged to refine and refine the people's ideas. Through these research results, it is judged that the Korean government will be able to contribute to inducing the policyization process through continuous public participation. In deriving success factors for policyization through public participation in the future, how influencing factors such as the public participation process, communication through online channels, and collaboration with experts affect the public participation process using quantitative analysis techniques A study to prove it will have to be conducted subsequently.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.5
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• pp.567-575
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• 2020

As online social networks are used as a critical medium for modern people's information sharing and relationship, their users are increasing rapidly every year. This not only increases usage but also surpasses the existing media in terms of information credibility. Therefore, emerging marketing strategies are deliberately attacking social networks. As a result, public opinion, which should be formed naturally, is artificially formed by online attacks, and many people trust it. Therefore, many studies have been conducted to detect agents attacking online social networks. In this paper, we analyze the trends of researches attempting to detect such online social network attackers, focusing on researches using social network graph characteristics. While the existing content-based techniques may represent classification errors due to privacy infringement and changes in attack strategies, the graph-based method proposes a more robust detection method using attacker patterns.

• Informatization Policy
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• v.20 no.2
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• pp.73-90
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• 2013

Rational debate and public conversation in the public sphere of social network are crucial conditions for realizing deliberative democracy. However, negative communication can occur online more frequently than in the real space, and mutually hostile messages are appearing. In the electoral process, citizens combining for particular candidates have made personal attacks against, abused and slandered the opposing candidates. Then, how and to what degree has the flaming behavior been appearing in the elections? Are there influencers to propagate the flaming behavior? And how flaming are these influencers, compared to internet users? This research focuses on the flaming behavior which occurred during the reelection for Seoul Mayor, in order to diagnose the role of social network as an online public sphere. This study analyzes the spreading degree of flaming messages depending on each issue, and the differences of messages between influencers and normal users. There was frequent flaming behaviors to distribute biased information which criticized, laughed at and maliciously attacked individual candidates. Moreover, influencers who advanced leading opinions, displayed a higher flaming degree than normal users.