• KIPS Transactions on Software and Data Engineering
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• v.10 no.1
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• pp.1-8
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• 2021

In the political field of news articles, there are polarized and biased characteristics such as conservative and liberal, which is called political bias. We constructed keyword-based dataset to classify bias of news articles. Most embedding researches represent a sentence with sequence of morphemes. In our work, we expect that the number of unknown tokens will be reduced if the sentences are constituted by subwords that are segmented by the language model. We propose a document embedding model with subword tokenization and apply this model to SVM and feedforward neural network structure to classify the political bias. As a result of comparing the performance of the document embedding model with morphological analysis, the document embedding model with subwords showed the highest accuracy at 78.22%. It was confirmed that the number of unknown tokens was reduced by subword tokenization. Using the best performance embedding model in our bias classification task, we extract the keywords based on politicians. The bias of keywords was verified by the average similarity with the vector of politicians from each political tendency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1825-1844
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• 2019

Political campaigns circulate manipulative opinions in online communities to implant false beliefs and eventually win elections. Not only is this type of manipulation unfair, it also has long-lasting negative impacts on people's lives. Existing tools detect political manipulation based on a supervised classifier, which is accurate when trained with large labeled data. However, preparing this data becomes an excessive burden and must be repeated often to reflect changing manipulation tactics. We propose a practical detection system that requires moderate groundwork to achieve a sufficient level of accuracy. The proposed system groups opinions with similar properties into clusters, and then labels a few opinions from each cluster to build a classifier. It also models each opinion with features deduced from raw data with no additional processing. To validate the system, we collected over a million opinions during three nation-wide campaigns in South Korea. The system reduced groundwork from 200K to nearly 200 labeling tasks, and correctly identified over 90% of manipulative opinions. The system also effectively identified transitions in manipulative tactics over time. We suggest that online communities perform periodic audits using the proposed system to highlight manipulative opinions and emerging tactics.

• The Journal of the Korea Contents Association
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• v.21 no.5
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• pp.157-169
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• 2021

YouTube has rapidly grown as a news media outlet. As political content without fact-checking is actively provided and YouTube algorithms are used for content recommendations, users are selectively exposed to certain political ideologies, which could escalate conflicts among political groups. In particular, the stronger the identification of in-group, the greater the antipathy toward outgroup, and the more exposed the content to the parties that support or oppose it, the stronger the identification or the antipathy can be. This study investigated the relationship between selective exposure and political attitude polarization in the context of political video on YouTube. Based on social identity theory, this study also found that political identification mediates the relationship between selective exposure and political attitude polarization.

• Journal of the Korean Society for information Management
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• v.35 no.3
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• pp.41-75
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• 2018

The purpose of this study is to analyze the characteristics of Korean media on the topic of archives & records management based on time-series analysis. In this study, from January, 1999 to June, 2018, 4,680 news articles on archives & records management topics were extracted from BigKinds. In order to examine the characteristics of the media coverage on the archives & records management topic, this study was analyzed to the difference of the press coverage by period, subject, and type of the media. In addition, this study was conducted word-frequency based content analysis and semantic network analysis to investigate the content characteristics of media on the subject. Based on these results, this study was analyzed to the differences of media coverage by period, subject, and type of media. As a result, the news in the field of records management showed that there was a difference in the amount of news coverage and news contents by period, subject, and type of media. The amount of news coverage began to increase after the Presidential Records Management Act was enacted in 2007, and the largest amount of news was reported in 2013. Daily newspapers and financial newspapers reported the largest amount of news. As a result of analyzing news reports, during the first 10 years after 1999, news topics were formed around the issues arising from the application and diffusion process of the concept of archives & records management. However, since the enactment of the Presidential Records Management Act, archives & records management has become a major factor in political and social issues, and a large amount of political and social news has been reported.

• Korean journal of communication and information
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• v.49
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• pp.57-80
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• 2010

This study examines how national newspapers interpret, evaluate and report the Korean grand canal and rebuilding four major rivers through the news writings. For this research, ChosunIlbo, the Hankyoreh Shinmun and HankukIlbo are selected. A total of 961 news writings are analyzed by using the concept of news frame designed by Gamson(1993). As a result, the findings are as follows: First, the most frequently reported news frame for ChosunIlbo is economic consequence; the Hankyoreh for ecological environment, and HankukIlbo for authoritative political execution by the administrative. Second, the most frequently interviewed group through all of the papers is the administrative and the ruling Grand National Party, the main body of rebuilding the Korean grand canal. On the country, voices of environmental protection groups, non-profit civic organizations and the ordinary people are reported rarely. Third, the ratio of authoritative political execution by the administrative and economic consequence are very high. Finally, in terms of the framing activity by the interviewed groups in the newspapers, ChosunIlb reports 'Outcome' the most frequently, the Hankyoreh does 'Loss-gain' & 'Process' and HankukIlbo 'Process' & 'Substantive'. Thus it concluded that ChosunIlbo does not play a role as a social mediator for the social disputes. However, the Hankyoreh and HankukIlbo try to represent environmental and civic organizations fairly.

• Korean journal of communication and information
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• v.41
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• pp.232-267
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• 2008

This study is a comparative analysis of news frames between Chosunilbo and Hankyereh which have shown contrastive political attitude. The coverage of two political scandal, the Prime Minister Lee Haechan's golf happening and an Assemblyman of opposition party Choi Yeonhee's sexual harassment were analysed. The two political scandals were occurred one after the other and had some similarities. But two newspapers showed very contrastive frame on the two political scandals. On the Prime Minister Lee's scandal Chosunilbo showed politicizing frame, lobby golf frame, immorality frame, resignation frame. In contrast Hankyereh used depoliticization frame and human error frame. On the Assemblyman Choi's scandal Hankyereh showed politicizing frame, personal responsibility frame, immorality frame, resignation frame. But Chosunilbo used social responsibility frame and human error frame. In conclusion two newspapers showed very contrastive coverage according to the respective political attitude.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.6
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• pp.875-885
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• 2018

This study analyzed the major issues of the Candlelight Rally and Taegukgi Rally registered in news comments of the politics section of the portal site from October 24, 2016 to March 19, 2017. We examined the political recognition of the two rallies with the Named Entity Recognition. The main analytical items are the responsibility for impeachment, the subject and method of settlement, and other major issues. As a result of the analysis, the comments of the Candlelight Rally focused on the impeachment support and the legal penalties of the regime ministers, and insisted on resolving the political situation through the next election after impeachment. The comments of the Taegukgi Rally focused on the rejection of the impeachment to maintain the regime and insisted on rejecting the impeachment of the Constitutional Court. The conflicts between the group that supported Candlelight Rallis and the group that supported Taegukgi rallies are predicted to last at least for the time being (Park Geun-hye's trial period) after the presidential election. After the impeachment of the President and replacement of the regime this conflict will develop into the confrontation between the pursuit of liquidation and new politics and the attempt to influence the trial of Park Geun-hye. Therefore, the efforts to integrate society in the aftermath are necessary.

• The Journal of the Convergence on Culture Technology
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• v.4 no.3
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• pp.87-92
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• 2018

This paper aims to investigate political stances of news producers or news organizations by analyzing editorials from two Korean newspapers, Chosun Ilbo and the Hankyoreh, which are totally different in ideology, both qualitatively and quantitatively. In particular, the headlines from 16 editorials and 14 editorials from the two newspapers respectively published from May 28 to June 27 were analyzed in terms of political stances to a U.S-North Korea Summit. Moreover, two editorials published right after the U.S-North Summit were quantitatively analyzed within Martin and White (2005)'s framework. As a result, it was found that Chosun ilbo showed a negative stance to the summit by employing the 'feeling' factor within an attitude component most frequently, whereas the Hankyoreh was overwhelmingly positive toward the issue and the dialogue expansion factor within an engagement component is most frequently used to deliver its positive stance toward the issue.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.105-112
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• 2020

The present study aims to explore news sharers' characteristic. Specifically, it aims to look at news sharers' demographic characteristics, old media news usage and new media news usage. Besides, it also explores factors affecting news sharing behavior. The study used the second data of Korea Press Foundation. Findings from surveys suggest that first, news sharers are younger and have higher education than not news sharers. Second, news sharers use less news through old media while more news through new media. Third, political orientation, portal, SNS and online video platform new usage, messenger news reliability have positive effects on news sharing, while age and portal news reliability have negative effects on it. Based on these findings, implication, limitations, and topics for future research are discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.4958-4970
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• 2019

As technology advances, the amount of fake news is increasing more and more by various reasons such as political issues and advertisement exaggeration. However, there have been very few research works on fake news detection, especially which uses grammatical transformation on deep neural network. In this paper, we shall present a new Fake News Detection Model, called FAGON(Fake news detection model using Grammatical transformation On deep Neural network) which determines efficiently if the proposition is true or not for the given article by learning grammatical transformation on neural network. Especially, our model focuses the Korean language. It consists of two modules: sentence generator and classification. The former generates multiple sentences which have the same meaning as the proposition, but with different grammar by training the grammatical transformation. The latter classifies the proposition as true or false by training with vectors generated from each sentence of the article and the multiple sentences obtained from the former model respectively. We shall show that our model is designed to detect fake news effectively by exploiting various grammatical transformation and proper classification structure.