• Annual Conference on Human and Language Technology
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• 2016.10a
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• pp.67-71
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• 2016

본 논문에서는 word2vec과 doc2vec을 함께 CNN에 적용한 문서 분류 방안을 제안한다. 먼저 어절, 형태소, WPM(Word Piece Model)을 각각 사용하여 생성한 토큰(token)으로 doc2vec을 활용하여 문서를 vector로 표현한 후, 초보적인 문서 분류에 적용한 결과 WPM이 분류율 79.5%가 되어 3가지 방법 중 최고 성능을 보였다. 다음으로 CNN의 입력자질로써 WPM을 이용하여 생성한 토큰을 활용한 word2vec을 범주 10개의 문서 분류에 사용한 실험과 doc2vec을 함께 사용한 실험을 수행하였다. 실험 결과 word2vec만을 활용하였을 때 86.89%의 분류율을 얻었고, doc2vec을 함께 적용한 결과 89.51%의 분류율을 얻었다. 따라서 제안한 모델을 통해서 분류율이 2.62% 향상됨을 확인하였다.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.835-838
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• 2000

Popular methods for extracting a text region in video images are in general based on analysis of a whole image such as merge and split method, and comparison of two frames. Thus, they take long computing time due to the use of a whole image. Therefore, this paper suggests the faster method of extracting a text region without processing a whole image. The proposed method uses line sampling methods, FFT and neural networks in order to extract texts in real time. In general, text areas are found in the higher frequency domain, thus, can be characterized using FFT The candidate text areas can be thus found by applying the higher frequency characteristics to neural network. Therefore, the final text area is extracted by verifying the candidate areas. Experimental results show a perfect candidate extraction rate and about 92% text extraction rate. The strength of the proposed algorithm is its simplicity, real-time processing by not processing the entire image, and fast skipping of the images that do not contain a text.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.4143-4159
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• 2015

We-the-media (aka wedia) is a concept where the users of social networking sites, such as Facebook, turn into the broadcasters. This study used the popular application Bitstrips as the experiment tool. Facebook was used as the Wedia platform for publishing designed comics, then used the three elements of Goffman's dramaturgy model-role, scene and dialog-to analyze 265 comics created by 3 researchers and observe the audience's responses within 9 months. The results showed that people want to see a good story with positive dialogue, and prefer scene is school more than work. As all these elements are controllable, Wedia communication has the potential for more applications. We also found that including the elements of news, gambling and gift-giving tended to trigger greater response. Furthermore, We suggesting that such embedding of product information in web episodes (webisodes) with caricature could be a successful marketing strategy.

• Journal of Contemporary Eastern Asia
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• v.20 no.2
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• pp.1-18
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• 2021

This study investigates the influence of social network services (SNS) and political podcasts on youth participation in candlelight rallies leading up to the impeachment of the Korean president. It also examines the effect of SNS and podcasts on online participation through SNSs. It was found that engaging in political discussions with friends or parents and news media use, including TV and Internet newspapers, exerted a major positive influence on participation in the rallies. However, SNS had a negative influence, while podcasts did not have a significant effect. On the other hand, SNS and podcasts had a positive influence on online participation. The results of structural equation modeling showed that SNS and podcasts affected SNS participation in the mediation of political discussion and political efficacy.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.1476-1478
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• 2013

최근 페이스북(Facebook), 트위터(Twitter) 등의 SNS(Social Network Service)의 사용자가 급격하게 증가하고 있다. SNS가 발달하면서 언제 어디서나 쉽게 자신의 위치, 현재의 감정들을 온라인상에서 공유한다. 이에 따라 사람의 감정을 표현하는 단어 100여개를 7가지 감정(기쁨, 흥미, 슬픔, 분노, 놀람, 지루함, 통증)으로 분류하였으며[1]. 이를 분석하기 위한 감정 표현 분석기 모듈을 설계하였다. 설계한 모듈을 사용하여 페이스북의 사용자 뉴스피드(News-Feed)를 분석하여 사용자의 성향을 분석하였다.

• Journal of Public Diplomacy
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• v.2 no.1
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• pp.43-68
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• 2022

Multiple modes of communication on social media can contribute to public diplomacy in informing, conversing, and networking with members of foreign publics. However, manipulative behaviours on social media, prevalent especially in high tension contexts, create disruptions to authentic communication in what could be grey/black propaganda or information warfare. This study reviews existing literature about models of public diplomacy to guide an empirical study of China's communication in the #SouthChinaSea conversation on Twitter. It uses computational methods to identify, record, and analyze one-way, two-way, and network communication of China's actors. It employs manual qualitative research to determine the nature of China's actors. On that basis, it assesses China's Twitter communication in the issue against various models of public diplomacy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.3
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• pp.1022-1034
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• 2023

Various aspects of artificial intelligence (AI) have become of significant interest to academia and industry in recent times. To satisfy these academic and industrial interests, it is necessary to comprehensively investigate trends in AI-related changes of diverse areas. In this study, we identified and predicted emerging convergences with the help of AI-associated research abstracts collected from the SCOPUS database. The bidirectional encoder representations obtained via the transformers-based topic discovery technique were subsequently deployed to identify emerging topics related to AI. The topics discovered concern edge computing, biomedical algorithms, predictive defect maintenance, medical applications, fake news detection with block chain, explainable AI and COVID-19 applications. Their convergences were further analyzed based on the shortest path between topics to predict emerging convergences. Our findings indicated emerging AI convergences towards healthcare, manufacturing, legal applications, and marketing. These findings are expected to have policy implications for facilitating the convergences in diverse industries. Potentially, this study could contribute to the exploitation and adoption of AI-enabled convergences from a practical perspective.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.541-544
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• 2021

본 논문은 어떤 기업의 주식 주문 정보를 담고 있는 호가창(limit order book)과 해당 기업과 관련된 뉴스 헤드라인을 사용하여 해당 기업의 주가 등락을 예측하는 딥러닝 기반 모델을 제안한다. 제안 모델은 호가창의 중기 변화와 단기 변화를 모두 고려하는 한편, 동기간 발생한 뉴스 헤드라인까지 예측에 고려함으로써 주가 등락 예측 정확도를 높인다. 제안 모델은 호가창의 변화의 특징을 CNN(convolutional neural network)으로 추출하고 뉴스 헤드라인을 Word2vec으로 생성된 단어 임베딩 벡터를 사용하여 나타낸 뒤, 이들 정보를 결합하여 특정 기업 주식의 다음 날 등락여부를 예측한다. NASDAQ 실데이터를 사용한 실험을 통해 제안 모델로 5개 종목(Amazon, Apple, Facebook, Google, Tesla)의 일일 주가 등락을 예측한 결과, 제안 모델은 기존 방법에 비해 정확도를 최대 17.14%, 평균 10.7% 향상시켰다.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.64-67
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• 2021

가짜뉴스는 뉴스 기사 형식을 갖는 날조된 정보를 의미하며, 최근 모바일 인터넷 장치의 보급과 소셜 네트워크 서비스의 대중화로 온라인 확산이 가속화되고 있다. 기존 연구는 가짜뉴스의 탐지를 위해 뉴스의 주제목, 부제목, 리드, 본문 등 뉴스 기사를 이루는 구성요소를 비롯하여 언론사, 기자, 날짜, 확산 경로 등의 메타 데이터를 대상으로 분석하였다. 그러나 뉴스의 제목과 본문 및 메타 데이터 등은 내용 수정이 쉬워, 다량의 데이터를 학습한 모델이라 하더라도 높은 정확도를 장기간 유지하기 어려울 수 있다. 이러한 문제점을 해결하기 위하여 본 논문은 합성곱 신경망을 이용해 문맥 정보를 분석하고 장단기 메모리 기반의 감성분석을 추가로 수행한다. 문맥 정보와 가짜뉴스 유포자가 쉽게 수정할 수 없는 감성 변화 패턴을 활용하여 성능이 개선된 가짜뉴스 탐지 모델을 제안한다.

• Journal of Science and Technology Studies
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• v.12 no.1
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• pp.145-183
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• 2012

Science reporting is easier to lead to failure than other news reporting because it needs higher professionalism. According to Actor-Network Theory(ANT), not only research results(artifacts) of scientists but also science articles are hybrid networks. Namely, they are connected by human actors(scientist, reporter, etc.) and nonhuman actors(press releases etc.). When the process of science reporting is examined on the view of ANT, it is the process that scientists' results translate the media via press releases as intermediaries and expand their network to the public. This study aims at making an ANT analysis of how research results of Electronics and Telecommunications Research Institute(ETRI) scientist Hyun-Tak Kim were reported by lots of media, focusing on the rhetoric of ETRI's press release. It can reveal the reason for the science reporting's failure and hint at the better science journalism.