• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.193-197
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• 2021

The pandemic situation caused by COVID-19 has a large and small impact on our society socially, economically, psychologically, and other aspects. In order to prevent the spread of COVID-19, various countries, including Korea, have entered into long-term home care and distance learning systems. However, distance learning experiments conducted in many countries have raised whether face-to-face education can be replaced by distance learning. Therefore, in this study, public opinion, social perception, and field trends were analyzed based on media reports on distance learning. For this purpose, 2,600 articles from 11 newspapers and four broadcasters related to distance learning were collected in this study. Based on this data, keyword trend analysis, topic modeling analysis, sentiment analysis were performed.

• The Journal of the Korea Contents Association
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• v.16 no.8
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• pp.1-9
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• 2016

In accordance with the increased political and social utilization of social media, demands on online trend analysis and monitoring technologies based on social bigdata are also increasing rapidly. In this paper, we define 'risk' as issues which have probability of turn to negative public opinion among big social issues and classify their types in details. To define risk types, we conduct a complete survey on news documents and analyzed characteristics according to issue domains. We also investigate cross-medias analysis to find out how different public media and personalized social media. At the result, we define 58 risk types for 6 domains and developed automatic classification model based on machine learning algorithm. Based on empirical experiments, we prove the possibility of automatic detection for social issue risk in social media.

• The Journal of the Korea Contents Association
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• v.17 no.11
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• pp.554-566
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• 2017

Through the Broadcasting Act, Republic of Korea regulates the broadcasting system to remain neutral regarding particular party or candidate. However, as MBC and JTBC reports the issue of President Park's impeachment in bisected way - conservative and progressive - the controversy aroused. This research paper comparatively analyzed each broadcasting company's evening news by focusing on quantity aspect, reporting tendency regarding trend of public opinion and mass rally and the news frame. Our research showed that both JTBC and MBC had partially reported; JTBC on pro-impeachment rally's side which was called candlelight rally, and MBC on anti-impeachment rally's side, called Korean National Flag rally. Regarding the way how they reported the impeachment, JTBC reported much more in depth than MBC, and MBC reported the process emotionally, standing for President Park.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.51-66
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• 2018

As AI (Artificial Intelligence) technologies have been swiftly evolved, a lot of products and services are under development in various fields for better users' experience. On this technology advance, negative effects of AI technologies also have been discussed actively while there exists positive expectation on them at the same time. For instance, many social issues such as trolley dilemma and system security issues are being debated, whereas autonomous vehicles based on artificial intelligence have had attention in terms of stability increase. Therefore, it needs to check and analyse major social issues on artificial intelligence for their development and societal acceptance. In this paper, multi-categorical sentiment analysis is conducted over online public opinion on artificial intelligence after identifying the trending topics related to artificial intelligence for two years from January 2016 to December 2017, which include the event, match between Lee Sedol and AlphaGo. Using the largest web portal in South Korea, online news, news headlines and news comments were crawled. Considering the importance of trending topics, online public opinion was analysed into seven multiple sentimental categories comprised of anger, dislike, fear, happiness, neutrality, sadness, and surprise by topics, not only two simple positive or negative sentiment. As a result, it was found that the top sentiment is "happiness" in most events and yet sentiments on each keyword are different. In addition, when the research period was divided into four periods, the first half of 2016, the second half of the year, the first half of 2017, and the second half of the year, it is confirmed that the sentiment of 'anger' decreases as goes by time. Based on the results of this analysis, it is possible to grasp various topics and trends currently discussed on artificial intelligence, and it can be used to prepare countermeasures. We hope that we can improve to measure public opinion more precisely in the future by integrating empathy level of news comments.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.91-94
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• 2018

감정분석은 텍스트에서 나타난 저자 혹은 발화자의 태도, 의견 등과 같은 주관적인 정보를 추출하는 기술이며, 여론 분석, 시장 동향 분석 등 다양한 분야에 두루 사용된다. 감정분석 방법은 사전 기반 방법, 기계학습 기반 방법 등이 있다. 본 논문은 사전 기반 감정분석에 필요한 한국어 감정사전 자동 구축 방법을 제안한다. 본 논문은 영어 감정사전으로부터 한국어 감정사전을 자동으로 구축하는 방법이며, 크게 세 단계로 구성된다. 첫 번째는 영한 병렬말뭉치를 이용한 영한사전을 구축하는 단계이고, 두 번째는 영한사전을 통한 이중언어 그래프를 생성하는 단계이며, 세 번째는 영어 단어의 감정값을 한국어 단어의 감정값으로 전파하는 단계이다. 본 논문에서는 제안된 방법의 유효성을 보이기 위해 사전 기반 한국어 감정분석 시스템을 구축하여 평가하였으며, 그 결과 제안된 방법이 합리적인 방법임을 확인할 수 있었으며 향후 연구를 통해 개선한다면 질 좋은 한국어 감정사전을 효과적인 방법으로 구축할 수 있을 것이다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.5
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• pp.567-575
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• 2020

As online social networks are used as a critical medium for modern people's information sharing and relationship, their users are increasing rapidly every year. This not only increases usage but also surpasses the existing media in terms of information credibility. Therefore, emerging marketing strategies are deliberately attacking social networks. As a result, public opinion, which should be formed naturally, is artificially formed by online attacks, and many people trust it. Therefore, many studies have been conducted to detect agents attacking online social networks. In this paper, we analyze the trends of researches attempting to detect such online social network attackers, focusing on researches using social network graph characteristics. While the existing content-based techniques may represent classification errors due to privacy infringement and changes in attack strategies, the graph-based method proposes a more robust detection method using attacker patterns.

• Journal of Internet of Things and Convergence
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• v.8 no.2
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• pp.41-48
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• 2022

This study tried to empirically explore which issues related to the social service agency for public(as below SSA), that is, social perceptions were formed, by using mess media related to the SSA. This study is meaningful in that it identifies the overall social perception and trend of SSA through public opinion. In order to extract media trend data, the search used the big data analysis system, Textom, to collect data from the representative portals Naver News and Daum News. The collected texts were 1,299 in 2020 and 1,410 in 2021, for a total of 2,709. As a result of the analysis, first, the most derived words in relation to the frequency of text appearance were 'SSA', 'establishment', and 'operation'. Second, as a result of the N-gram analysis, the pairs of words directly related to the SSA 'SSA and public', 'SSA and opening', 'SSA and launch', and 'SSA and Department Director', 'SSA and Staff', 'SSA and Caregiver' etc. Third, in the results of TF-IDF analysis and word network analysis, similar to the word occurrence frequency and N-gram results, 'establishment', 'operation', 'public', 'launch', 'provided', 'opened', ' 'Holding' and 'Care' were derived. Based on the above analysis results, it was suggested to strengthen the emergency care support group, to commercialize it in detail, and to stabilize jobs.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.372-376
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• 2006

현재 심각한 재해에 대한 임박성은 일부 관계자 이외는 감지하지 못하고 있는 것이 현실이다. 재해와 같은 위기에 관한 지식이나 이에 대처하기 위한 기술은 어린 시절부터 습득해 두어야 할 기초적 지식 및 능력이라고 생각한다. 그럼에도 불구하고 대지진 발생이 임박하고 있음을 타인의 일처럼 생각하고 있다는 점은 재해와 같은 위기를 자신의 일처럼 생각하고 어떻게 대처해야 할 것인가에 대해 스스로 생각할 수 있는 기회가 충분하지 않다는 것에서 유래한다. 즉 체계적 실천적인 방재 위기관리교육이 충분하게 실시되지 않고 있다는 점을 지적할 수 있을 것이다. 특히 지역주민의 생명 신체 재산을 보호해야 하는 지방자치단체의 소방담당직원의 실천적 대응능력은 말할 것도 없고 수장(首長)의 리스크 관리능력에 대해 의구심을 가지고 있다. 또한 지역 자체의 방재력 강화라는 관점에서는 자주방재조직 등의 지역방재리더나 지역주민 개개인의 방재능력을 향상시켜야 할 필요성이 강조되고 있다. 최근에 건설된 신관저를 계기로 변화된 방재 위기관리 시스템에 관한 정책적 동향을 살펴본다. 아울러 방재 위기관리에 대한 인재양성을 위한 교육의 일환으로 구축된 e-Learning System인 e-College의 구성 및 관련 내용을 살펴봄으로써 정책적 시사점을 도출하고자 한다. 지방자치단체의 방재 위기관리에 있어서 수장 등 간부직원의 의식과 자세가 지역의 방재력을 크게 좌우하는 것으로 볼 수 있다. 방재담당직원 소방직단원에 대한 교육과제를 들 수 있겠다. 고도로 도시화된 사회가 재해에 대한 취약성이 높아지고 있다. 지역의 방재리더, 재해자원봉사, 주민에 대한 교육과제로 도도부현, 시정촌, 대학에서 방재 위기관리 교육이 실시되고 있지만, 1999년 총리부(總理府)에서 여론조사를 보면 자주방재활동에 참가한 경험이 없는 사람이 전체 70%를 차지하고 있다. 기업에 대한 교육과제로 재해발생시에 사원이나 고객의 안전 확보, 사업의 피해경감 조기복구에 의한 경제에 대한 영향을 경감하기 위한 준비를 충실히 해야 한다.

• Journal of the Korean Society for Marine Environment & Energy
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• v.6 no.3
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• pp.3-15
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• 2003

The concept of 'Cleaner Production(CP)' and various activities aiming at promoting CP are investigated along with the applicabilities of CP to marine environment. Although the conventional approaches dealing with the marine pollutions can be absorbed in CP, the whole activities of Production and conservation in the ocean must be projected into a new Paradigm, 'Sustainable Development.' Renewable energy is the first key to a complete CP and the ocean can provide us with the clew. In order to introduce CP system more effectively to marine environment opinion collection, environment monitoring, problem identification, resolution proposition, state-of-the-art evaluation, policy development, communication, education and public information are to be Planned and followed up systematically KOSMEE is believed to be a good structure to stand at the center of the upcoming CP activities in the ocean.

• Journal of the Korea Convergence Society
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• v.11 no.5
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• pp.199-207
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• 2020

Recently, big data analysis has drawn attention in various fields as it can generate value from large amounts of data and is also used to run political campaigns or predict results. However, existing research had limitations in compiling information about candidates at a high-level by analyzing only specific SNS data. Therefore, this study analyses news trends, topics extraction, sentiment analysis, keyword analysis, comment analysis for the 2017 presidential election of South Korea. The results show that various topics had been generated, and online opinions are extracted for trending keywords of respective candidates. This study also shows that portal news and comments can serve as useful tools for predicting the public's opinion on social issues. This study will This paper advances a building strategic course of action by providing a method of analyzing public opinion across various fields.