• Title/Summary/Keyword: naver trend

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Examining the Disparity between Court's Assessment of Cognitive Impairment and Online Public Perception through Natural Language Processing (NLP): An Empirical Investigation (Natural Language Processing(NLP)를 활용한 법원의 판결과 온라인상 대중 인식간 괴리에 관한 실증 연구)

  • Seungkook Roh
    • The Journal of Bigdata
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    • v.8 no.1
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    • pp.11-22
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    • 2023
  • This research aimed to examine the public's perception of the "rate of sentence reduction for reasons of mental and physical weakness" and investigate if it aligns with the actual practice. Various sources, such as the Supreme Court's Courtnet search system, the number of mental evaluation requests, and the number of articles and comments related to "mental weakness" on Naver News were utilized for the analysis. The findings indicate that the public has a negative opinion on reducing sentences due to mental and physical weakness, and they are dissatisfied with the vagueness of the standards. However, this study also confirms that the court strictly applies the reduction of responsibility for individuals with mental disabilities specified in Article 10 of the Criminal Act based on the analysis of actual judgments and the number of requests for psychiatric evaluation. In other words, even though the recognition of perpetrators' mental disorders is declining, the public does not seem to recognize this trend. This creates a negative impact on the public's trust in state institutions. Therefore, law enforcement agencies, such as the police and prosecutors, need to enforce the law according to clear standards to gain public trust. The judiciary also needs to make a firm decision on commuting sentences for mentally and physically infirm individuals and inform the public of the outcomes of its application.

A Study on Solving ESG Issues focusing on Pet Problems (메타버스에서의 반려동물을 중심으로 한 ESG 문제 해결 설계)

  • Eunjin Kim;Woori Kim;Seunghoon Choi;Nayoon Song;Hyunseo Jang;Jinsil Ahn;Mingu Lee;Juhvun Eune
    • Smart Media Journal
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    • v.13 no.5
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    • pp.52-61
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    • 2024
  • The onset of the COVID-19 pandemic has accelerated social transformations across various nations. These changes, particularly prominent in the corporate and industrial sectors, have necessitated a shift towards increased remote activities, fundamentally altering societal structures. Within this context, the concept of the Metaverse, a virtual world existing since the early 2000s but previously underrecognized, began to gain widespread recognition. In South Korea, major tech companies such as Naver, Kakao, and Coupang have long normalized remote working, with new employee orientations also taking place on Metaverse platforms. Beyond the IT sector, institutions requiring large gatherings, such as schools, have adopted the Metaverse for hosting major events like welcome ceremonies and informational sessions. This phenomenon suggests that the Metaverse is not merely a transient social trend but is gradually integrating into the daily lives of the general populace, serving as a significant social connector. This study explores the potential of Metaverse-enabled design thinking and methodologies to address the Environmental, Social, and Governance (ESG) challenges faced by Korean society. Specifically, the research focuses on developing solutions for social issues related to pets in Korea.

A study on Korean tourism trends using social big data -Focusing on sentiment analysis- (소셜 빅데이터를 활용한 한국관광 트렌드에 관한연구 -감성분석을 중심으로-)

  • Youn-hee Choi;Kyoung-mi Yoo
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.3
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    • pp.97-109
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    • 2024
  • In the field of domestic tourism, tourism trend analysis of tourism consumers, both international tourists and domestic tourists, is essential not only for the Korean tourism market but also for local and governmental tourism policy makers. e will explore the keywords and sentiment analysis on social media to establish a marketing strategy plan and revitalize the domestic tourism industry through communication and information from tourism consumers. This study utilized TEXTOM 6.0 to analyze recent trends in Korean tourism. Data was collected from September 31, 2022, to August 31, 2023, using 'Korean tourism' and 'domestic tourism' as keywords, targeting blogs, cafes, and news provided by Naver, Daum, and Google. Through text mining, 100 key words and TF-IDF were extracted in order of frequency, and then CONCOR analysis and sentiment analysis were conducted. For Korean tourism keywords, words related to tourist destinations, travel companions and behaviors, tourism motivations and experiences, accommodation types, tourist information, and emotional connections ranked high. The results of the CONCOR analysis were categorized into five clusters related to tourist destinations, tourist information, tourist activities/experiences, tourism motivation/content, and inbound related. Finally, the sentiment analysis showed a high level of positive documents and vocabulary. This study analyzes the rapidly changing trends of Korean tourism through text mining on Korean tourism and is expected to provide meaningful data to promote domestic tourism not only for Koreans but also for foreigners visiting Korea.

A Study on Comics Outreach Programs for Contents marginalized Areas (콘텐츠 소외지역의 만화 아웃리치 프로그램 모델링 연구)

  • Lee, Seung-Jin
    • Cartoon and Animation Studies
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    • s.49
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    • pp.359-382
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    • 2017
  • Content is the complex of art and technology of trend, so it is important to experience different technologies for content education. Today, many non-profit organizations plan and operate numbers of programs for disabilities, low-income, and minority families to enhance the quality of life and the realization of social integration. These programs are limited to museums and galleries, not so pro-actively in progressing. Various contend education is necessary to the expansion of cultural exchange for the culturally alienated area. Naver is running an outreach program named . It is an experience-based outreach program where current cartoon / webtoon writers come directly to the school to inform students about the basic story of comics and comic techniques. However, the fact that the is not centered on the marginalized area but is centered on the Seoul Gyeonggi area, has the limitation that they can not benefit from a wide range of programs because they have a space limit of 'school', and, has a spatial limitation that the experience of the work is excluded. 'Outreach programs in marginalized areas' must be reorganized into a fluid dimension, not a fixed, single-system program. You should be able to experience and experience your work by directly using various professional equipment of comics based on your capacity and experience, local culture, religion, and society. These program participants will gain the effect of attractive and effective learning with empathy with their comic experience. Meanings of Comics content outreach program are following: First, the rich cultural archive can be used efficiently by providing various contents to existing outreach programs with the educational limitation of museums and galleries. Second, Comics contents can be enjoyed as a part of our life by understanding diversity and technology of contents. Third, because it is the program of expertise' participation, it can remodel, and restructure the severed experience in remote areas for the continuous growth and development, and furthermore, it can enhance the understanding of society.

Analysis of media trends related to spent nuclear fuel treatment technology using text mining techniques (텍스트마이닝 기법을 활용한 사용후핵연료 건식처리기술 관련 언론 동향 분석)

  • Jeong, Ji-Song;Kim, Ho-Dong
    • Journal of Intelligence and Information Systems
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    • v.27 no.2
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    • pp.33-54
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    • 2021
  • With the fourth industrial revolution and the arrival of the New Normal era due to Corona, the importance of Non-contact technologies such as artificial intelligence and big data research has been increasing. Convergent research is being conducted in earnest to keep up with these research trends, but not many studies have been conducted in the area of nuclear research using artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. This study was conducted to confirm the applicability of data science analysis techniques to the field of nuclear research. Furthermore, the study of identifying trends in nuclear spent fuel recognition is critical in terms of being able to determine directions to nuclear industry policies and respond in advance to changes in industrial policies. For those reasons, this study conducted a media trend analysis of pyroprocessing, a spent nuclear fuel treatment technology. We objectively analyze changes in media perception of spent nuclear fuel dry treatment techniques by applying text mining analysis techniques. Text data specializing in Naver's web news articles, including the keywords "Pyroprocessing" and "Sodium Cooled Reactor," were collected through Python code to identify changes in perception over time. The analysis period was set from 2007 to 2020, when the first article was published, and detailed and multi-layered analysis of text data was carried out through analysis methods such as word cloud writing based on frequency analysis, TF-IDF and degree centrality calculation. Analysis of the frequency of the keyword showed that there was a change in media perception of spent nuclear fuel dry treatment technology in the mid-2010s, which was influenced by the Gyeongju earthquake in 2016 and the implementation of the new government's energy conversion policy in 2017. Therefore, trend analysis was conducted based on the corresponding time period, and word frequency analysis, TF-IDF, degree centrality values, and semantic network graphs were derived. Studies show that before the 2010s, media perception of spent nuclear fuel dry treatment technology was diplomatic and positive. However, over time, the frequency of keywords such as "safety", "reexamination", "disposal", and "disassembly" has increased, indicating that the sustainability of spent nuclear fuel dry treatment technology is being seriously considered. It was confirmed that social awareness also changed as spent nuclear fuel dry treatment technology, which was recognized as a political and diplomatic technology, became ambiguous due to changes in domestic policy. This means that domestic policy changes such as nuclear power policy have a greater impact on media perceptions than issues of "spent nuclear fuel processing technology" itself. This seems to be because nuclear policy is a socially more discussed and public-friendly topic than spent nuclear fuel. Therefore, in order to improve social awareness of spent nuclear fuel processing technology, it would be necessary to provide sufficient information about this, and linking it to nuclear policy issues would also be a good idea. In addition, the study highlighted the importance of social science research in nuclear power. It is necessary to apply the social sciences sector widely to the nuclear engineering sector, and considering national policy changes, we could confirm that the nuclear industry would be sustainable. However, this study has limitations that it has applied big data analysis methods only to detailed research areas such as "Pyroprocessing," a spent nuclear fuel dry processing technology. Furthermore, there was no clear basis for the cause of the change in social perception, and only news articles were analyzed to determine social perception. Considering future comments, it is expected that more reliable results will be produced and efficiently used in the field of nuclear policy research if a media trend analysis study on nuclear power is conducted. Recently, the development of uncontact-related technologies such as artificial intelligence and big data research is accelerating in the wake of the recent arrival of the New Normal era caused by corona. Convergence research is being conducted in earnest in various research fields to follow these research trends, but not many studies have been conducted in the nuclear field with artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. The academic significance of this study is that it was possible to confirm the applicability of data science analysis technology in the field of nuclear research. Furthermore, due to the impact of current government energy policies such as nuclear power plant reductions, re-evaluation of spent fuel treatment technology research is undertaken, and key keyword analysis in the field can contribute to future research orientation. It is important to consider the views of others outside, not just the safety technology and engineering integrity of nuclear power, and further reconsider whether it is appropriate to discuss nuclear engineering technology internally. In addition, if multidisciplinary research on nuclear power is carried out, reasonable alternatives can be prepared to maintain the nuclear industry.