• Title/Summary/Keyword: research topic analysis

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Analysis of User Reviews for Webtoon Applications Using Text Mining (텍스트 마이닝을 활용한 웹툰 애플리케이션 사용자 리뷰 분석)

  • Shin, Hyorim;Choi, Junho
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.4
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    • pp.457-468
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    • 2022
  • With the rapid growth of the webtoon industry, a new model for webtoon applications has emerged. We have entered the era of webtoon application version 3.0 after ver 1.0 and ver 2.0. Despite these changes, research on user review analysis for webtoon applications is still insufficient. Therefore, this study aims to analyze user reviews for 'Kakao Webtoon (Daum Webtoon)' that presented the webtoon application 3.0 model. For analysis, 20,382 application reviews were collected and pre-processed, and TF-IDF, network analysis, topic modeling, and emotional analysis were conducted for each version. As a result, the user experience of the webtoon application for each version was analyzed and usability testing conducted.

A Study on the News Frame of COVID-19 Vaccine through Structural Topic Modeling and Semantic Network Analysis

  • Eun-Ji Yun;Bo-Young Kang
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.5
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    • pp.129-153
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    • 2023
  • This study was conducted in the context of the Covid-19 pandemic by analyzing a large amount of press report frames regarding the Covid-19 vaccine which is of great public interest, in order to explore the role and direction of trusted media as core elements of crisis communication. The study period lasted for eight months beginning in November 2020 when the development of the Covid-19 vaccine was in progress until June 2021. Set-up as research subjects were the Chosun Ilbo, Joongang Ilbo, Dong-A Ilbo and Hankyoreh according to their public confidence rankings and number of readers.The analysis method used structured topic Modeling (STM) and semantic network analysis. As a result, based on a clear cluster of word structures and a central analysis value, a total of 64 relevant frames, 16 for each news company, were gathered. In the third phase a comparative analysis of the four news companies was carried out to verify the organizational degree of the frames and substantial differences.

Analysis of Trends in Science Gifted Education Using Topic Modeling (토픽 모델링을 활용한 과학영재교육 연구동향 분석)

  • Kim, Hye Won;Jhun, Youngseok
    • Journal of Korean Elementary Science Education
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    • v.40 no.3
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    • pp.283-294
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    • 2021
  • The purpose of this study is to examine the trends of science gifted education-related research for the last 5 years using LDA topic modeling. To achieve the purpose of the study, 2,404 keywords of 292 domestic academic papers were analyzed using RISS, KISS, and DBpia. The main results were as follows. First, the number of researches in science gifted education has been decreasing since 2019. In the science gifted education research, the top 10 keywords were 'students', 'program', 'elementary school', 'class', 'creativity', 'gifted education', 'awareness', 'teacher', 'education', and 'activity'. Second, as a result of topic modeling analysis, 10 topics were derived. Research topics mainly conducted in science gifted education for the past five years are 'Affective characteristics of science gifted students', 'Characteristics of science gifted students in middle school', 'Development and application of science gifted education programs', 'Education programs of science gifted high school', 'Cognitive characteristics of science gifted students', 'Policy of science gifted education', 'Science gifted students and creativity', 'Research conducting education by science gifted students', 'Academic and career choice of science gifted students', 'Science concept of science gifted Students'. In the past, the proportion of specific topics was relatively high, but the proportion between topics does not differ significantly as 2019 approaches. Therefore, it can be confirmed that the more recent it comes, the more research is being conducted evenly without being biased toward one subject.

Trend Analysis of the Agricultural Industry Based on Text Analytics

  • Choi, Solsaem;Kim, Junhwan;Nam, Seungju
    • Agribusiness and Information Management
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    • v.11 no.1
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    • pp.1-9
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    • 2019
  • This research intends to propose the methodology for analyzing the current trends of agriculture, which directly connects to the survival of the nation, and through this methodology, identify the agricultural trend of Korea. Based on the relationship between three types of data - policy reports, academic articles, and news articles - the research deducts the major issues stored by each data through LDA, the representative topic modeling method. By comparing and analyzing the LDA results deducted from each data source, this study intends to identify the implications regarding the current agricultural trends of Korea. This methodology can be utilized in analyzing industrial trends other than agricultural ones. To go on further, it can also be used as a basic resource for contemplation on potential areas in the future through insight on the current situation. database of the profitability of a total of 180 crop types by analyzing Rural Development Administration's survey of agricultural products income of 115 crop types, small land profitability index survey of 53 crop types, and Statistics Korea's survey of production costs of 12 crop types. Furthermore, this research presents the result and developmental process of a web-based crop introduction decision support system that provides overseas cases of new crop introduction support programs, as well as databases of outstanding business success cases of each crop type researched by agricultural institutions.

Research trend analysis of Korean new graduate nurses using topic modeling (토픽모델링을 활용한 신규간호사 관련 국내 연구동향 분석)

  • Park, Seungmi;Lee, Jung Lim
    • The Journal of Korean Academic Society of Nursing Education
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    • v.27 no.3
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    • pp.240-250
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    • 2021
  • Purpose: The aim of this study is to analyze the research trends of articles on just graduated Korean nurses during the past 10 years for exploring strategies for clinical adaptation. Methods: The topics of new graduate nurses were extracted from 110 articles that have been published in Korean journals between January 2010 and July 2020. Abstracts were retrieved from 4 databases (DBpia, RISS, KISS and Google scholar). Keywords were extracted from the abstracts and cleaned using semantic morphemes. Network analysis and topic modeling were performed using the NetMiner program. Results: The core keywords included 'education', 'training', 'program', 'skill', 'care', 'performance', and 'satisfaction'. In recent articles on new graduate nurses, three major topics were extracted by Latent Dirichlet Allocation (LDA) techniques: 'turnover', 'adaptation', 'education'. Conclusion: Previous articles focused on exploring the factors related to the adaptation and turnover intentions of new graduate nurses. It is necessary to conduct further research focused on various interventions at the individual, task, and organizational levels to improve the retention of new graduate nurses.

Language Model Adaptation Based on Topic Probability of Latent Dirichlet Allocation

  • Jeon, Hyung-Bae;Lee, Soo-Young
    • ETRI Journal
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    • v.38 no.3
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    • pp.487-493
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    • 2016
  • Two new methods are proposed for an unsupervised adaptation of a language model (LM) with a single sentence for automatic transcription tasks. At the training phase, training documents are clustered by a method known as Latent Dirichlet allocation (LDA), and then a domain-specific LM is trained for each cluster. At the test phase, an adapted LM is presented as a linear mixture of the now trained domain-specific LMs. Unlike previous adaptation methods, the proposed methods fully utilize a trained LDA model for the estimation of weight values, which are then to be assigned to the now trained domain-specific LMs; therefore, the clustering and weight-estimation algorithms of the trained LDA model are reliable. For the continuous speech recognition benchmark tests, the proposed methods outperform other unsupervised LM adaptation methods based on latent semantic analysis, non-negative matrix factorization, and LDA with n-gram counting.

Overlap Analysis of Research Areas in Four Library and Information Science Journals (문헌정보학 분야 4개 학술지의 연구영역 중첩분석)

  • Yoo Kyung Jeong
    • Journal of the Korean Society for information Management
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    • v.40 no.4
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    • pp.259-277
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    • 2023
  • This study aims to identify the academic landscape of the field of Library and Information Science by analyzing the research areas of the four major domestic journals using structural topic modeling and network analysis. The results show that each journal focuses on different research areas. The Journal of the Korean Society for Library and Information Science covers the most comprehensive range of research areas in the field, while the Journal of the Korean Biblia Society for Library and Information Science shows a similar research trend but with a higher preference for research areas related to library management and library programs. The Journal of Korean Library and Information Science Society deals more with topics related to school libraries and reading education and the Journal of the Korean Society for Information Management focuses more on information technology and information science. This study is able to provide valuable foundational data for researchers in submitting their papers and for the topical specialization and diversification of the journals in the field of Library and Information Science.

Unified Psycholinguistic Framework: An Unobtrusive Psychological Analysis Approach Towards Insider Threat Prevention and Detection

  • Tan, Sang-Sang;Na, Jin-Cheon;Duraisamy, Santhiya
    • Journal of Information Science Theory and Practice
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    • v.7 no.1
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    • pp.52-71
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    • 2019
  • An insider threat is a threat that comes from people within the organization being attacked. It can be described as a function of the motivation, opportunity, and capability of the insider. Compared to managing the dimensions of opportunity and capability, assessing one's motivation in committing malicious acts poses more challenges to organizations because it usually involves a more obtrusive process of psychological examination. The existing body of research in psycholinguistics suggests that automated text analysis of electronic communications can be an alternative for predicting and detecting insider threat through unobtrusive behavior monitoring. However, a major challenge in employing this approach is that it is difficult to minimize the risk of missing any potential threat while maintaining an acceptable false alarm rate. To deal with the trade-off between the risk of missed catches and the false alarm rate, we propose a unified psycholinguistic framework that consolidates multiple text analyzers to carry out sentiment analysis, emotion analysis, and topic modeling on electronic communications for unobtrusive psychological assessment. The user scenarios presented in this paper demonstrated how the trade-off issue can be attenuated with different text analyzers working collaboratively to provide more comprehensive summaries of users' psychological states.

Analysis of research status on domestic AI education (국내 인공지능 교육에 대한 연구 현황 분석)

  • Park, Mingyu;Han, Kyujung;Sin, Subeom
    • Journal of The Korean Association of Information Education
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    • v.25 no.5
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    • pp.683-690
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    • 2021
  • The purpose of this study is to identify research trends on artificial intelligence education. We analyzed 164 domestic journal papers related to AI education published since 2016. The criteria for papers analysis are number of publications by year, journal name, research topic, research type, data collection method, research subject, and subject. The main research areas and areas that require further research are reviewed. The method of the study was analyzed based on the topic and summary of the selected papers, but the text was checked if it was unclear. As a result of the study, research on 'artificial intelligence education' started in earnest after 2017, and has been rapidly increasing in recent years. As a result of the analysis, there were many studies on artificial intelligence education programs and content development, and artificial intelligence perception and image. As for the type of research, there were many quantitative studies, and the development research method was used a lot as a data collection method. In the study subjects, elementary school had a high proportion, and in subject, it was found that there were many practicial subject(technology) dealing with artificial intelligence contents.

Analysis of Breaking Research Trends in Korea (국내 브레이킹 연구동향 분석)

  • Yoo, Hyun-Mee
    • The Journal of the Korea Contents Association
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    • v.22 no.3
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    • pp.468-475
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    • 2022
  • The purpose of this study is to identify trends in domestic breaking research to derive characteristics and implications, and further suggest future research directions. To this end, literature analysis (the timing of paper publication, research method, research topic) and keyword analysis of 50 papers related to breaking published in academic journals registered with the Korea Research Foundation (KCI) were conducted. The research results are as follows. First, the trend by thesis publication period was first published in 2006, showed a slight increase in 2012, and then increased rapidly in 2021. Second, domestic braking-related research has been mainly focused on qualitative research (60%). Third, looking at the research topic, it is divided into three categories: identity establishment, culture and arts field, and sports field, of which studies related to identity establishment accounted for more than 60%. Finally, looking at the keywords frequently used in breaking papers, the most frequently appeared word was 'hip-hop', followed by 'culture'. Based on these results, implications were drawn to establishing the identity of braking through academic and theoretical approaches, practical approaches through the development of standardized textbooks and curriculum, strengthening the characteristics and capabilities of the field through integrated approaches, and changing to sports.