• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.2
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• pp.23-35
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• 2007

With the development of semantic web technologies in information retrieval area, the necessity for thesaurus is recently increasing along with internet lexicons. A thesaurus is the combination of classification and a lexicon, and is the topic map of knowledge structure expressing relations among concepts(terms) subject to human knowledge activities such as learning and research using formally organized and controlled index terms for clarifying the context of superordinate and subordinate concepts. However, although thesaurus are regarded as essential tools for controlling and standardizing terms and searching and processing information efficiently, we do not have a Korean thesaurus for geology. To build a thesaurus, we need standardized and well-defined guidelines. The standardized guidelines enable efficient information management and help information users use correct information easily and conveniently. The present study purposed to build a thesaurus system with terms used in geology. For this, First, we surveyed related works for standardizing geological terms in Korea and other countries. Second, we defined geological topics in 15 areas and prepared a classification system(draft) for each topic. Third, based on the geological thesaurus classification system, we created the specification of geological thesaurus. Lastly, we designed and implemented an internet-based geological thesaurus system using the specification.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.1
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• pp.393-413
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• 2021

Digital humanities, which creates new and innovative knowledge through the combination of digital information technology and humanities research problems, can be seen as a representative multidisciplinary field of study. To investigate the intellectual structure of the digital humanities field, a network analysis of authors and keywords co-word was performed on a total of 441 papers in the last two years (2019, 2020) at the Digital Humanities Conference. As the results of the author and keyword analysis show, we can find out the active activities of Europe, North America, and Japanese and Chinese authors in East Asia. Through the co-author network, 11 dis-connected sub-networks are identified, which can be seen as a result of closed co-authoring activities. Through keyword analysis, 16 sub-subject areas are identified, which are machine learning, pedagogy, metadata, topic modeling, stylometry, cultural heritage, network, digital archive, natural language processing, digital library, twitter, drama, big data, neural network, virtual reality, and ethics. This results imply that a diver variety of digital information technologies are playing a major role in the digital humanities. In addition, keywords with high frequency can be classified into humanities-based keywords, digital information technology-based keywords, and convergence keywords. The dynamics of the growth and development of digital humanities can represented in these combinations of keywords.

• Journal of Korea Society of Industrial Information Systems
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• v.26 no.6
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• pp.47-60
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• 2021

Since the outbreak of COVID-19 in 2019, the pandemic has been prolonged. This study compares and analyzes the degree of social media usage, the information type of posts (infectious disease information, promote action, psychological communication), and the level of user engagement in conducting crisis communication by country. We conduct text analysis by collecting information on Facebook and YouTube posts from January 2020 to March 2021 of disease control and prevention agencies in Korea, US, UK, and EU. As a result, the use of social media in Korea and US is higher than of the UK and EU, and all four countries are using social media as a means to provide infectious disease information and to promote action. Although social media can be a means to reach the public psychologically, such as sympathy and respect, there are no posts of psychological communication type on social media in countries other than the US. User engagement with posts is highest in the promotion action type. This study can help define the importance and role of social media in establishing an infectious disease crisis communication strategy.

• 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.

• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.11-21
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• 2022

All-solid-state batteries are one of the promising candidates for next-generation batteries and are drawing attention as a key component that will lead the future electric vehicle industry. This study analyzes 10,280 comments on Reddit, which is a global social media, in order to identify policy issues and public interest related to all-solid-state batteries from 2016 to 2021. Text mining such as frequency analysis, association rule analysis, and topic modeling, and sentiment analysis are applied to the collected global data to grasp global trends, compare them with the South Korean government's all-solid-state battery development strategy, and suggest policy directions for its national research and development. As a result, the overall sentiment toward all-solid-state battery issues was positive with 50.5% positive and 39.5% negative comments. In addition, as a result of analyzing detailed emotions, it was found that the public had trust and expectation for all-solid-state batteries. However, feelings of concern about unresolved problems coexisted. This study has an academic and practical contribution in that it presented a text mining analysis method for deriving key issues related to all-solid-state batteries, and a more comprehensive trend analysis by employing both a top-down approach based on government policy analysis and a bottom-up approach that analyzes public perception.

• The Journal of Bigdata
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• v.7 no.2
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• pp.113-128
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• 2022

After COVID-19, interest in "sustainable tourism" increased, and the number of tourists who wanted to experience "sustainable tourism" also increased. However, there is a problem that the programs and methods for 'sustainable tourism' are not specific and diverse. In addition, since most of the interests of "sustainable tourism" focus on "environment" and "carbon neutrality," there are not many programs or government policies that can contribute to the community. Therefore, in this study, news data and review data were analyzed to suggest a method for promoting 'sustainable tourism'. First, in this study, major themes of sustainable travel were derived through news big data analysis. Through this analysis, policy themes and events of 'sustainable tourism' were derived. By analyzing news big data related to "sustainable tourism," we would like to analyze the reasons why sustainable travel has not been activated in Korea. Finally, in order to promote sustainable travel in Jeju island, we analyzed user review data of Jeju local currency, and propose a idea to coexist with the local community.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.11
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• pp.1-11
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• 2009

A content based pub/sub (Publish/subscribe) services at the peer-to-peer network has the requirements about how to distribute contents information of subscriber and to delivery the events efficiently. For satisfying the requirements, a DHT(Distributed Hash Table) based pub/sub overlay networking and tree type topology based network construction using filter technique have been proposed. The DHT based technique is suitable for topic based pub/sub service but it's not good contents based service that has the variable requirements. And also filter based tree topology networking is not efficient at the environment where the user requirements are distributed. In this paper we propose the R-Tree algorithm based pub/sub overlay network construction method. The proposed scheme provides cost effective event delivery method by mapping user requirement to multi-dimension and hierarchical grouping of the requirements. It is verified by simulation at the variable environment of user requirements and events.

• Journal of Cadastre & Land InformatiX
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• v.50 no.2
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• pp.101-115
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• 2020

In this paper, big data analysis method was used to find out global trends in autonomous driving and to derive activate spatial information services. The applied big data was used in conjunction with news articles and patent document in order to analysis trend in news article and patents document data in spatial information. In this paper, big data was created and key words were extracted by using LDA (Latent Dirichlet Allocation) based on the topic model in major news on autonomous driving. In addition, Analysis of spatial information and connectivity, global technology trend analysis, and trend analysis and prediction in the spatial information field were conducted by using WordNet applied based on key words of patent information. This paper was proposed a big data analysis method for predicting a trend and future through the analysis of the connection between the autonomous driving field and spatial information. In future, as a global trend of spatial information in autonomous driving, platform alliances, business partnerships, mergers and acquisitions, joint venture establishment, standardization and technology development were derived through big data analysis.

• Journal of Science Education
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• v.32 no.2
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• pp.1-16
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• 2008

The purpose of this study was to analyze about STS contents in the next generation science textbook for 10th grade according to curriculum revision 2007 and high school science textbooks focused on the Earth Science which were published according to the 7th curriculum. The contents of STS were analyzed by the STS topics of Yager(1989), Piel's standard(1981), and student activities by SATIS. The results of this study are the same as follows: 'The next generation science textbook' was shown that 20.9% is STS material amount in average by Yager's standard. 'High school science textbooks' were shown that 11.3% is STS material amount in average. Based on the STS topics by Yager's standard, most of STS content is focused on 'Relativity with local community', 'Application of science' and 'Cooperative work on real problems'. However, there is rare contents such as 'Multiple dimensions of science', 'Practice with decision-making strategies' and 'Evaluation concerned for getting and using information' in the next generation science textbook. In high school science textbooks were shown that 'Applicability of science' is the highest and 'Relativity with local community' is the next high contents. Based on the STS topics by Piel's standard, most of STS contents are focused on 'Environmental quality', 'Space research' and 'National defence' in the next generation science textbook. But high school science textbooks are focused on 'Natural resources' and 'Technology development'. The activities were analyzed by SATIS student activities. The major categories of activities included in the next generation science textbook were 'Investigation', 'Simulation' and 'Data analysis'. But, there were rare activities like 'Roleplaying', 'Research design' and 'Simulation' in high school science textbooks.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.4
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• pp.5-22
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• 2021

This study aimed to understand how people perceive the transition from offline to online classes at universities during the COVID-19 pandemic. To achieve the goal, we collected tweets related to online classes on Twitter and performed sentiment and time series topic analysis. We have the following findings. First, through the sentiment analysis, we found that there were more negative than positive opinions overall, but negative opinions had gradually decreased over time. Through exploring the monthly distribution of sentiment scores of tweets, we found that sentiment scores during the semesters were more widespread than the ones during the vacations. Therefore, more diverse emotions and opinions were showed during the semesters. Second, through time series topic analysis, we identified five main topics of positive tweets that include class environment and equipment, positive emotions, places of taking online classes, language class, and tests and assignments. The four main topics of negative tweets include time (class & break time), tests and assignments, negative emotions, and class environment and equipment. In addition, we examined the trends of public opinions on online classes by investigating the changes in topic composition over time through checking the proportions of representative keywords in each topic. Different from the existing studies of understanding public opinions on online classes, this study attempted to understand the overall opinions from tweet data using sentiment and time series topic analysis. The results of the study can be used to improve the quality of online classes in universities and help universities and instructors to design and offer better online classes.