• Journal of Technology Innovation
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• v.23 no.4
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• pp.151-175
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• 2015

The general public is a key stakeholder in the science and technology domain. However, traditional approaches require substantial efforts and resources to analyze how does the general public understand science and technology issues. We applied the topic modeling, a form of text clustering, to the texts about the nuclear power which were posted on an online space in order to explore the general public's thoughts on the issue. This study investigates the extent to which macro-level events influence understandings of the general public on the science and technology issues and weather these changes in understandings are sustained over time. It examines the possibility of applying topic modeling in narrowing a perception gap between the general public and the experts through a near-real-time monitoring of the public interests and perceptions about the science and technology issues.

• Journal of the Korean Data and Information Science Society
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• v.26 no.5
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• pp.1167-1173
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• 2015

The development of information and communication technology like SNS, blogs, and bulletin boards, was provided a variety of places where you can express your thoughts and comments and allowing Big Data to grow, many people reveal the opinion of the social issues in SNS such as Twitter. In this study, we would like to pre-built sentimental dictionary about social issues and conduct a sentimental analysis with structured dictionary, to gather opinions on social issues that are created on twitter. The data that I used is "bikini", "nakkomsu" including tweet. As the result of analysis, precision is 61% and F1- score is 74%. This study expect to suggest the standard of dictionary construction allowing you to classify positive/negative opinion on specific social issues.

• Annual Conference on Human and Language Technology
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• 2009.10a
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• pp.61-66
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• 2009

본 논문은 다양한 형태의 웹 문서에 적용하기 위해서, 언어의 통계정보 및 후처리 규칙에 기반 하여 개선된 문장경계 인식 기술을 제안한다. 제안한 방법은 구두점 생략 및 띄어쓰기 오류가 빈번한 웹 문서에 적용하기 위해서 문장경계로 사용될 수 있는 모든 음절을 대상으로 학습하여 문장경계 인식을 수행하였고, 문장경계인식 성능을 최대화 하기 위해서 다양한 실험을 통해 최적의 자질 및 학습데이터를 선정하였고, 다양한 기계학습 기반 분류 모델을 비교하여 최적의 분류모델을 선택하였으며, 학습데이터에 의존적인 통계모델의 오류를 규칙에 기반 해서 보정하였다. 성능 실험은 다양한 형태의 문서별 성능 측정을 위해서 문어체와 구어체가 복합적으로 사용된 신문기사와 블로그 문서(평가셋1), 문어체 위주로 구성된 세종말뭉치와 백과사전 본문(평가셋2), 구두점 생략 및 띄어쓰기 오류가 빈번한 웹 사이트의 게시판 글(평가셋3)을 대상으로 성능 측정을 하였다. 성능척도로는 F-measure를 사용하였으며, 구두점만을 대상으로 문장경계 인식 성능을 평가한 결과, 평가셋1에서는 96.5%, 평가셋2에서는 99.4%를 보였는데, 구어체의 문장경계인식이 더 어려움을 알 수 있었다. 평가셋1의 경우에도 규칙으로 후처리한 경우 정확률이 92.1%에서 99.4%로 올라갔으며, 이를 통해 후처리 규칙의 필요성을 알 수 있었다. 최종 성능평가로는 구두점만을 대상으로 학습된 기본 엔진과 모든 문장경계후보를 인식하도록 개선된 엔진을 평가셋3을 사용하여 비교 평가하였고, 기본 엔진(61.1%)에 비해서 개선된 엔진이 32.0% 성능 향상이 있음을 확인함으로써 제안한 방법이 웹 문서에 효과적임을 입증하였다.

• Journal of Digital Contents Society
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• v.18 no.3
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• pp.585-592
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• 2017

As development of personal devices have made everyday use of internet much easier than before, it is getting generalized to find information and share it through the social media. In particular, communities specialized in each field have become so powerful that they can significantly influence our society. Finally, businesses and governments pay attentions to reflecting their opinions in their strategies. The stock market fluctuates with various factors of society. In order to consider social trends, many studies have tried making use of bigdata analysis on stock market researches as well as traditional approaches using buzz amount. In the example at the top, the studies using text data such as newspaper articles are being published. In this paper, we analyzed the post of 'Paxnet', a securities specialists' site, to supplement the limitation of the news. Based on this, we help researchers analyze the sentiment of investors by generating a domain-specific sentiment lexicon for the stock market.

• Journal of Korean Society of Archives and Records Management
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• v.18 no.3
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• pp.165-191
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• 2018

The National Archives of Korea and other archives now provide services through social media such as Facebook or Twitter, and use such platforms to interact with users. To be specific, users communicate with and get information from these archives via the National Sinmoongo, the place for civil petition. Therefore, it is significant to understand the users' needs and the contents of the communication by analyzing the comments and petitions that have appeared in these channels. For this, this study analyzed users' perceptions and information needs shared through social media and the National Sinmoongo of the National Archives of Korea. The social media content analyzed here were posts and comments from the Facebook accounts of the National Archives of Korea, e-Record, the Busan Archives, and the Presidential Archives of Korea. Also, sentences containing the words "National Archives of Korea" and "Presidential Archives of Korea" that have appeared in texts in the National Sinmoongo were analyzed. Based on the analysis results, suggestions that could activate the user-centered archival information services in the archives and records centers were made.

• Journal of Digital Convergence
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• v.9 no.3
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• pp.95-104
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• 2011

This study explored how political figures build their image using twitters. To examine the research question, this study analyzed twitter messages in five political figures: Si-Min, Yu, Jung-hee, Lee, Mun-soo, Kim, and Young-gil, Song. The findings showed that except for Mrs. Lee, the other political figures presented more one-way messages than two-way messages in twitters. Even though twitter has benefits of communicating instantly and two-way communication between followers and followings, most messages in their twitters were limited to informative message. The study also classified the messages into social-oriented and individual-oriented in each politician' s twitter. The result presented that Mrs. Lee twitter included individual-oriented messages, but the other three political figures had more social-oriented messages.

• Journal of The Korean Association of Information Education
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• v.25 no.4
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• pp.633-640
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• 2021

Education related issues are social problems in which various groups and situations are intricately linked to each other. It is difficult to find issues by analyzing social phenomena related to education. Korean based text analysis can be analyzed in a quantitative. With the development of text analysis techniques, research results have been recently achieved, and it can be fully utilized to derive educational issues from text data in Korean. In this study, petition articles in the field of childcare/education were collected on the online-board of the Blue House National Petition website, and text analysis was used to derive issues in the education world. The analysis derived 6 topics through Latent Dirichlet Allocation(LDA) among topic modeling techniques. The association rules of major keywords were analyzed and visualized as graphs. In addition to deriving educational issues through the existing questionnaire, it can provide implications for future research directions and policies in that issues can be sufficiently discovered through text-based analysis methods.

• The Journal of the Korea Contents Association
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• v.19 no.2
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• pp.135-146
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• 2019

This study was designed to analyze trends in the entire convergence research beyond academic research through social media big data analysis at a time when interdisciplinary convergence research is emphasized along with the fourth industrial revolution. For this purpose, about 150,000 cases of texts and titles were acquired for about 10 years from January 2009 to September 2018 in connection with the convergence research in social media, and word cloud and network analysis were conducted. As a results, the research fields that were actively conducted for each period were eco-tech in 2009 and 2010, smart technology in 2011 and 2012, information and communication in 2013 and 2014, robots in 2015 and 2016, and artificial intelligence in 2017 and 2018. Also, the research areas that have been consistently conducted for about 10 years are culture, design, chemistry, nanotechnology, biotechnology, robot, IT, and information and communication. Since this study identifies trends in convergence research over time, it can be helpful to researchers who are planning convergence research direction by understanding the trends of convergence research.

• Journal of Creative Information Culture
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• v.6 no.2
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• pp.57-64
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• 2020

As the information society gradually advances, various opinions overflow and their complexity increases. As the results, it was made more difficult to derive important issues and properly respond to those problems. Accordingly, it is necessary to get a handle on emerging problems in education in addition to existing discourses and issues. This study aimed at examining the issues of education by analyzing the petitions posted under 'parenting and education' category on National Petition board. In order to offer objective and detailed results, we employed the topic modeling based LDA algorithm, which is an effective method to extract topics in multiple documents. Nine topics were derived as the result of the analysis and the relationship among those topics was visualized. The values of this study exist in that the derived topics represent important issues that reflect the public opinions.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.4
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• pp.165-170
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• 2022

By reducing time spent outside, a shopping system was developed for middle-aged and elderly people who mainly use neighborhood marts and neighborhood mart managers. The main functions of this app are direct shopping and online shopping, and it was developed using QR code using Zxing library on Android and Kakao Map using Kakao API. In addition, it provides information such as payment statistics and bulletin board posts that members need through recycler view and graphs in an easy-to-read manner. Through this system, members can efficiently manage by reducing fatigue when using the mart through direct purchase using QR code and delivery through map, and reducing manpower wastage as a mart manager. Also, as a mart manager, more consumers will be able to sell more items.