• Korean Journal of Artificial Intelligence
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• v.12 no.2
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• pp.9-16
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• 2024

In this study, we delve into the effects of personalization algorithms on the creation of "filter bubbles," which can isolate individuals intellectually by reinforcing their pre-existing biases, particularly through personalized Google searches. By setting up accounts with distinct ideological learnings-progressive and conservative-and employing deep neural networks to simulate user interactions, we quantitatively confirmed the existence of filter bubbles. Our investigation extends to the deployment of an LSTM model designed to assess political orientation in text, enabling us to bias accounts deliberately and monitor their increasing ideological inclinations. We observed politically biased search results appearing over time in searches through biased accounts. Additionally, the political bias of the accounts continued to increase. These results provide numerical evidence for the existence of filter bubbles and demonstrate that these bubbles exert a greater influence on search results over time. Moreover, we explored potential solutions to mitigate the influence of filter bubbles, proposing methods to promote a more diverse and inclusive information ecosystem. Our findings underscore the significance of filter bubbles in shaping users' access to information and highlight the urgency of addressing this issue to prevent further political polarization and media habit entrenchment. Through this research, we contribute to a broader understanding of the challenges posed by personalized digital environments and offer insights into strategies that can help alleviate the risks of intellectual isolation caused by filter bubbles.

• The Journal of the Korea Contents Association
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• v.21 no.5
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• pp.1-10
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• 2021

This study empirically confirmed 'the political bias of the YouTube recommendation algorithm' and 'the selective exposure of user' to verify the Filter Bubble phenomenon of YouTube. For the experiment, two new YouTube accounts were opened and each account was trained simultaneously in a conservative and a liberal account for a week, and the "Recommended" videos were collected from each account every two days. Subsequently, through the text mining method, the goal of the research was to investigate whether conservative videos are more recommended in a righties account or lefties videos are more recommended in a lefties account. And then, this study examined if users who consumed political news videos via YouTube showed "selective exposure" received selected information according to their political orientation through a survey. As a result of the Text Mining, conservative videos are more recommended in the righties account, and liberal videos are more recommended in the lefties account. Additionally, most of the videos recommended in the righties/lefties account dealt with politically biased topics, and the topics covered in each account showed markedly definitive differences. And about 77% of the respondents showed selective exposure.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.495-508
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• 2023

To compare whether broadcast fact-checking news, which aims to overcome the limitations of objective reporting, ensures fairness, we analyzed 227 fact-checked news stories aired on the main news of KBS, MBC SBS, TV Chosun, JTBC MBN, and YTN from January 1, 2022 to May 31, 2022, when the 20th presidential and local election campaigns were held. The analysis showed clear differences in fact-checking targets and narratives by broadcasters. In general, MBC, JTBC,and YTN were more likely to favor liberal parties such as the Democratic Party, while TV Chosun had a lot of narratives favoring the conservative camp. SBS and MBN were relatively neutral. KBS seemed to be trying to remain outwardly neutral. SBS and TV Chosun were the most active in fact-checking, but they covered a wide range of issues and were characterized by a bias toward contextualizing issues that viewers were curious about, rather than clarifying the facts. The projection of ideological bias by broadcasters in fact-checking narratives is a challenge that needs to be overcome.

• 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.

• 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.

• Korean journal of communication and information
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• v.71
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• pp.274-298
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• 2015

Doctoral Candidate, Department of Communication, Pusan National University This study analyzed the political and social significance of the disaster accident news with the frame and bias concept. In particular, this study confirmed theoretically how domestic media biased frame when it presents problem definition, causing interpretation, moral evaluation, and post-prescription on the ferry Sewol accident, In addition, the bias of the frame was analyzed comparing what is the difference between the conservative newspapers and liberal newspapers. Findings are as follows. First, in diagnosis of ferry Sewol accident, news slanted fragmentation frame>personalization frame>authority-disorder frame. The Chosun Ilbo focus on fragmentation bias, meanwhile Hankyoreh focus on the authority disorder relatively. Second, in accident evaluation, responsibility frame> moral frame> problem-solution frame. The Chosun Ilbo focus on responsibility frame and moral frame. But Hankyoreh focus on responsibility frame and problem-solution frame. Third, in the matter of responsibility, government frame>personal frame>organizational frame. Chosun Ilbo biased responsibility of the government and individuals, while the Hankyoreh is relatively more emphasis on government responsibility and the responsibility of the organization also showed. Fourth, in problem solving, thematic frame and episodic frame bias appeared as rough and level. Chosun Ilbo showed episodic frame, Hankyoreh showed thematic frame. News frame and bias as well as ideological differences of media on ferry Sewol accident was discussed in the context of the social dimension.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.466-479
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• 2021

Fake news is flooded with fake news that mixes untrue falsehoods in whole or in part. In order to create a frame for political and social purposes, news is mainly created by combining facts with fakes, or news is created for the purpose of incitement to encourage distortion and hatred. In particular, some media, including over-the-air broadcasting, are expressing their political bias in a specific direction without hesitation. Even if the press has political bias, if it is based on the delivery of facts, a trusted media environment can be achieved under the mutual checks of conservatives and progressives. The May 18 Democratic Uprising is a painful history and fact of modern history, leaving remuneration and progress. Nevertheless, there is still a view that the May 18 Democratic Uprising is regarded as 'democracy movement' and 'violence'. This study analyzed how the conservative JoongAng Ilbo and the progressive Kyunghyang Shinmun Manpyeong deal with the May 18 Democratic Uprising. The Manpyeong of the two newspapers differs greatly from the viewpoint of the May 18 Democratic Uprising. The liberal tendency of the Kyunghyang Shinmun Manpyeong has great significance in that it reveals the essence of the event and satirizes the subject. On the other hand, the conservative JoongAng Ilbo Manpyeong cannot approach the nature of the case or the object of satire due to ambiguity.