• 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.

• Science of Emotion and Sensibility
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• v.23 no.4
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• pp.3-20
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• 2020

The purpose of this study was to investigate the effect of aging on visuo-spatial attention allocation ability and emotional perception bias. We used the useful field of view (UFOV) task to measure the visuo-spatial attention allocation ability and the emotional perception task to measure positive and negative emotional perception bias. A total of 48 participants took part in this study with 23 participants in the senior group and 25 in the junior group. The senior group showed slower response time and lower accuracy than the junior group in the UFOV task, indicating that the senior group had lower visuo-spatial attention allocation ability than the junior group. In the emotional perception task, the senior group showed both positive and negative emotional perception bias more than the junior group. The correlation analysis showed that the negative emotional perception bias for accuracy in the emotional perception task showed a positive correlation with the response time to the stimuli presented in the visual angle 30° in the UFOV task (r=.289). In addition, positive emotional perception bias for the accuracy in the emotional perception task showed a positive correlation with the accuracy of the stimuli presented in the visual angles 10°, 20°, and 30° in the UFOV task (r=.305, r=.322, and r=.299, respectively). However, it showed a negative correlation with the response time of the stimuli presented in the same location in the UFOV task (r=-.345, r=-.295, r=-.308). These results suggest that aging is associated with a decrease in the visuo-spatial attention allocation ability and perceptual bias toward positive and negative emotions. In addition, the positive and negative emotional perception biases associated with aging are potentially related to the reduced visuo-spatial attention allocation ability.

• The Journal of the Korea Contents Association
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• v.13 no.3
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• pp.162-173
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• 2013

This study was to examine the effect of trust, stigma, optimistic bias on risk perception of nuclear power plants. For this study, we carried out a survey targeting residents, total of 383, living in Seoul. The findings showed that trust of general public on nuclear power plants influenced negatively on stigma. Second, trust of general public on nuclear power plants influenced not significantly on optimistic bias. Third, stigma of general public on nuclear power plants influenced positively on risk perception. Fourth, optimistic bias of general public on nuclear power plants influenced negatively on risk perception.

• Annual Conference on Human and Language Technology
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• 2023.10a
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• pp.539-545
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• 2023

초거대 언어모델은 심화된 언어적 이해를 요구하는 여러 분야에 높은 영향력을 미치고 있으나, 그에 수반되는 편향성과 윤리성에 대한 우려 또한 함께 증대되었다. 특히 편향된 언어모델은 인종, 성적 지향 등과 같은 다양한 속성을 가진 개인들에 대한 편견을 강화시킬 수 있다. 그러나 이러한 편향성에 관한 연구는 대부분 영어 문화권에 한정적이며 한국어에 관한 연구 또한 한국에서 발생하는 지역 갈등, 젠더 갈등 등의 사회적 문제를 반영하지 못한다. 이에 본 연구에서는 ChatGPT의 내재된 편향성을 도출하기 위해 의도적으로 다양한 페르소나를 부여하고 한국의 사회적 쟁점들을 기반으로 프롬프트 집합을 구성하여 생성된 문장의 독성을 분석하였다. 실험 결과, 특정 페르소나 또는 프롬프트에 관해서는 지속적으로 유해한 문장을 생성하는 경향성이 나타났다. 또한 각 페르소나-쟁점에 대해 사회가 갖는 편향된 시각이 모델에 그대로 반영되어, 각 조합에 따라 생성된 문장의 독성 분포에 유의미한 차이를 보이는 것을 확인했다.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.05a
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• pp.451-454
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• 2020

딥러닝 기술을 이용한 정치적 성향의 편향성 분류를 위하여 신문 뉴스 기사를 수집하고, 머신러닝을 위한 학습 데이터를 구축하였다. 학습 데이터의 구축은 보수 성향과 진보 성향을 대표하는 6개 언론사의 뉴스에서 정치적 성향을 이진 분류 데이터로 구축하였다. 뉴스 기사의 수집 방법으로 최근 이슈들 중에서 정치적 성향과 밀접하게 관련이 있는 키워드 15개를 선정하고 이에 관한 뉴스 기사들을 수집하였다. 그 결과로 11,584개의 학습 및 실험용 데이터를 구축하였으며, 정치적 편향성 분류를 위한 머신러닝 모델을 설계하였다. 머신러닝 기법으로 학습 및 실험을 위해 형태소 단위의 임베딩을 이용하여 문장 및 문서 임베딩으로 확장하였으며, SVM(Support Vector Machine)을 이용하여 정치적 편향성 분류 실험을 수행한 결과로 75%의 정확도를 달성하였다.

• 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.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.2
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• pp.41.2-41.2
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• 2014

고립된 은하주위의 위은하들의 편향된 낙하 운동을 보인다. 이 편향성을 결정하는 요소는 속도가위장의 비등방성인데 속도가위장의 단축으로 위은하들의 낙하가 일어나는 관측적 증거를 제시하고 이 편향성을 측정하여 은하단과 은하의 동력학적 질량을 결정한 후 궁극적으로 중력 법칙을 검증한다.

• Journal of Korean Library and Information Science Society
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• v.36 no.1
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• pp.173-193
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• 2005

The modern society is one of knowledge and information, and the library is one of the important routes through which they are obtained. But the collection in the library, from the onset of its creation and the process of accumulation, could only be bent and biased due to the prejudice and distortion, inevitably acting as an agent that mires the essence of the library as a distribution channel for knowledge and information of modern society. This study is the discussion about the necessity, main assignment and the methodology of library collection study. The collection study needs to focus on the process of accumulating the collection in the library to track down the Process of becoming biased.

• Smart Media Journal
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• v.13 no.2
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• pp.44-51
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• 2024

The construction of a stress measurement detaset plays a curcial role in various modern applications. In particular, for the efficient training of artificial intelligence models for stress measurement, it is essential to compare various biases and construct a quality-controlled dataset. In this paper, we propose the construction of a stress measurement dataset with quality management through the comparison of various biases. To achieve this, we introduce strss definitions and measurement tools, the process of building an artificial intelligence stress dataset, strategies to overcome biases for quality improvement, and considerations for stress data collection. Specifically, to manage dataset quality, we discuss various biases such as selection bias, measurement bias, causal bias, confirmation bias, and artificial intelligence bias that may arise during stress data collection. Through this paper, we aim to systematically understand considerations for stress data collection and various biases that may occur during the construction of a stress dataset, contributing to the construction of a dataset with guaranteed quality by overcoming these biases.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2001.05a
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• pp.26-31
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• 2001

긍/부정 선택 실험에서 나타나는 뇌파 변화를 연구하였다. 서로 다른 위치에서 측정된 뇌파의 시공간적 상호관계를 정량화하는 변수로, 시간영역에서 계산하기 용이한 동기율(synchronization rate), 편향성(synchronization rate), 편향성(polarity), 상호상관(cross-correlation) 등의 변수를 도입하여, 긍/부정 선택 순간의 뇌파 변화를 살펴보았다. 좌우 전전두엽(Fp1, Fp2)에서 특정된 뇌파를 사용하여 계산한 동기율, 편향성의 평균과 요동폭, 상호상관 등은, 선택 순간 근처에서, 평상시에 뇌파와 통계적으로 유의미한 차이를 보였다.