• 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.

• Korean journal of communication and information
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• v.39
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• pp.178-223
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• 2007

The polarization of public opinion by regionalism is one of biggest problems in Korean society. This study attempts to examine the polarization of public opinion between two typical cities representing regionalism and explore the factors influencing on the polarization. The results show that the polarization of public opinion is based on the perceived public opinion rather than the real public opinion. The polarization of public opinion is greater with regional issue than national issue. In general, citizens of Pusan have a conservative bias in estimating other Pusan citizens' opinion and a liberal bias in estimating Gwangju citizens' opinion, whereas citizens of Gwangju have a looking-glass perception in estimating other Gwangju citizens' opinion and a conservative bias in estimating Pusan citizens' opinion. There are no significant differences of the real public opinion and the perceived opinion across three generations. But within each generation, the tendency of public opinion polarization is found between regions and is not shown to change over generations. Regression analyses show that individual's opinion and region are highly predictable variables that explain the perceived public opinion and the perception bias such as false consensus and pluralistic ignorance.

• Korean journal of communication and information
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• v.56
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• pp.7-25
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• 2011

The purpose of this paper is to start off a debate in the current situation in which there exists two different logics about a newspaper company expanding their business field to the broadcasting market. In order to analyze the implications of the phenomenon, three points are raised and analyzed. First, Chosun-Ilbo, Jungang-Ilbo and Donga-Ilbo, who had a permission to get into the broadcasting arena, did not make their logic based on the fact while deriving the public opinion to be optimistic. Second, they strictly held their frames in order to support their logics which were an overall deregulation, to stimulate the economy and to create jobs without introducing various perspectives. Third, broadcasting of three major newspaper companies could monopolize the public sphere rather than contributing to the diversity of public opinions against three existing broadcasting companies KBS, MBC, SBS.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.412-415
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• 2018

헌재, 대부분의 여론조사는 전통적 여론 조사 방식을 사용하고 있다. 그러나 이 방식은 온라인 상에서의 여론을 반영하지 못한다는 문제점이 존재한다. 따라서 이를 해결하고 온라인 상에서의 여론을 반영하기 위해, 비정형 뉴스 데이터를 이용한 지지율 분석 방안을 제안하고자 한다. 이 연구에서는 제안 방안을 알아보고 기존의 방식과 비교한 장단점, 시사점, 개선방안 등을 알아봄으로써 새로운 여론조사 방식의 제안을 목적으로 한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.682-683
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• 2014

최근 IT업체들은 온라인 상에서 소비자들이 평소에 쏟아내는 의견들을 수집, 축적해서, 원하는 키워드를 중심으로 내용을 분석함으로써, 특정 주제에 대해 어떤 여론이 형성되고 있으며, 여론이 어떻게 전파되고 있는지 경로를 파악할 수 있는 소셜 빅데이터 분석 툴을 경쟁적으로 개발하고 있다. 본 논문에서는 소셜 빅 데이터를 분석함에 있어 이슈를 감지하고 예측하는 기술을 실제 사례에 적용하여 분석한 결과를 고찰해 보고자 한다. 소셜 미디어 데이터 패턴을 비교 분석하고 부정이슈 감지를 위해 부정 여론을 확산시키는데 영향을 미치는 내용과 작성자를 독립변수로 하고, 평균 이슈 도달 시간 및 속도를 종속변수로 정의한다. 부정 여론 형성의 영향력은 트윗수, 리트윗 수를 기준으로 이슈 감지한다. 분석결과 전체 트윗 중 리트윗 메시지가 큰 비중 차지하고 이슈에 대한 버즈가 증가할수록 리트윗 비중이 증가하였으며 크게 확산될 때는 리트윗량이 크게 증가하여 짧은 시간 안에 넓게 확산하였다.

• Korean journal of communication and information
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• v.56
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• pp.194-218
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• 2011

Focusing on the individuals' structural positions and roles in the internet discussion network, this research explores whether and how the opinion leaders' network characteristics are associated with the message quality and interpersonal influence in terms of attention-drawing and response-generation, which prior studies often failed to fully explicate. Findings suggest that discussion participants with high message quality occupy more central positions in the discussion network, thus enjoy more attention and responses of other following participants. However, opinion leader's network centralities, which tap the structural positions and unique roles in the online discussion network, systematically mediate the effect of the message quality on interpersonal influence. Moreover, significant interaction between opinion perception and network centrality was found only on the majority opinion group, rendering the entire discussion structure toward more enclaved deliberation and group polarization. Taken together, the results imply that the influence of the online opinion leader can only be substantiated with participant's central positions in the discussion network, which has been ignored by the prior opinion leadership research.

• 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.

• 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 Korea Information Processing Society Conference
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• 2015.04a
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• pp.291-293
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• 2015

최근 스마트폰 사용자와 SNS를 이용하는 사용자들이 늘어나고 있다. 또 다양한 SNS가 등장하면서 SNS데이터의 양이 방대해지고 SNS데이터의 가치와 신뢰성도 점점 높아지고 있다. 이러한 SNS 데이터를 사용하여 특정 키워드의 여론을 분석하고 사용자들의 반응을 얻는 것은 좋은 정보로 여러 분야에 사용될 수 있을 것이다. 본 논문에서는 SNS를 기반으로 오피니언 마이닝을 사용해 특정 키워드에 대한 SNS사용자들의 여론을 분석하였다. 그 결과 실시간으로 올라오는 글들에 대하여 해당 키워드가 어떤 여론을 가지고 있는지 분석 결과를 얻었다.

• Korean Journal of Forensic Psychology
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• v.13 no.1
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• pp.23-52
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• 2022

In this study, focused group interviews with 24 incumbent judges were conducted on how they conceptualize public opinion and what attitude they take toward it in relation to judicial trials. The contents of the interviews were analyzed through grounded theory and topic modeling (STM). According to the grounded theory results, judges distinguished concepts such as social rules, socially accepted ideas, legal emotion, and public mood from public opinion, and subdivided public opinion into temporary and emotional reactions to specific legal cases and consistent attitudes toward law and policies. In addition, it was found that judges' attitudes toward public opinion and social norms differed depending on the type of cases or legal issues. Topic modeling results significantly corresponded to the grounded theory results. In this model, the effects of the types of cases dedicated to participants on topical prevalence were statistically significant.