• Title/Summary/Keyword: Topic network analysis

Search Result 389, Processing Time 0.026 seconds

Analyzing the Study Trends of 'Sense of Place' Using Text Mining Techniques (텍스트마이닝 기법을 활용한 국내외 장소성 관련 연구동향 분석)

  • Lee, Ina;Kim, Hea-Jin
    • Journal of the Korean BIBLIA Society for library and Information Science
    • /
    • v.30 no.2
    • /
    • pp.189-209
    • /
    • 2019
  • Main Path Analysis (MPA) is one of the text mining techniques that extracts the core literature that contributes knowledge transfer based on citation information in the literature. This study applied various text mining techniques to abstract of the paper related with sense-of-place, which is published at Korea and abroad from 1990 to 2018 so that could discuss in a macro perspective. The main path analysis results showed that from 1990, overseas research on sense-of-place has been carried out in the order of personal identity, public land management, environmental education and urban development-related areas. Also, by using the network analysis, this study found that sense-of-place was discussed at various levels in Korea, including urban development, culture, literature, and history. On the other hand, it has been found that there are few topic changes in international studies, and that discussions on health, identity, landscape and urban development have been going on steadily since the 1990s. This study has implications that it presents a new perspective of grasping the overall flow of relevant research.

Knowledge Visualization and Mapping of Studies on Social Systems Theory in Social Sciences: Focused on Niklas Luhmann (사회과학 분야 사회적 체계 이론 연구의 지식 시각화와 매핑 - Niklas Luhmann을 중심으로 -)

  • Park, Seongwoo;Hong, Soram
    • Journal of the Korean Society for Library and Information Science
    • /
    • v.56 no.1
    • /
    • pp.253-275
    • /
    • 2022
  • Niklas Luhmann is one of the most contentious and difficult theorist in sociology but follow-up studies on his theory gradually increase for recent 10 years. The purpose of this study is to observe how follow-up studies use the difficult concepts of Luhmann. Unlike previous studies, this study adopted a keyword rather than an article as the unit of analysis because keywords are linguistic constructs that can make concepts observable. The study analyzed co-occurrence of keywords in 139 articles retrieved from social sciences category in Web of Science DB. The key findings were following: the most important keywords were the name of Luhmann(Niklas Luhmann) and theory(social systems); keywords were grouped into 4 clusters(social systems theory, systems theory, legal system and political system, the significant of Luhmann's theory from the viewpoint of the history of social theory); topic terms were systems theory, communication, Autopoiesis, risk, legal system, functional differentiation, environment, social theory, sociological theory, structural coupling, systems and evolution. The significance of the study is following: the study gives keywords as useful access point for beginners of Luhmann's theory; the study proves that content analysis by keywords network can be applied to trend analysis of difficult theoretical researches.

A Study on Recent Research Trend in New Product Development Using Keyword Network Analysis (키워드 네트워크 분석을 이용한 NPD 연구의 진화 및 연구동향)

  • Pyun, JeBum;Jeong, EuiBeom
    • Journal of Korea Society of Industrial Information Systems
    • /
    • v.23 no.5
    • /
    • pp.119-134
    • /
    • 2018
  • Today, many firms face the environment of high uncertainty and severe competition due to the rapid technology development and the diverse needs of customers. In the business environment, one of the most important ways to gain sustainable competitive advantage and future growth engine is related to NPD (New Product Development), which is a very important issue for practice and academia. Thus, this study intends to provide new values to practitioners and researchers related to NPD by analyzing current research trends and future trends in NPD field. For this, we bibliometrically analyzed keyword networks which consist of keywords that were already published in the eminent journals from Scopus database to generate insights that have not been captured in the previous reviews on the topic. As a result, we could understand the extant research streams in NPD field, and suggest the changes of specific research topics based on the connected relationships among keywords over the time. In addition, we also foresaw the general future research trends in NPD field based on the keywords according to preferential attachment processes. Through this study, it was confirmed that NPD keyword network is a small world network that follows the distribution of power law and the growth of network is formed by link formation by keyword preferential attachment. In addition, through component analysis and centrality analysis, keywords such as Innovation, New product innovation, Risk management, Concurrent engineering, Research and development, and Product life cycle management are highly centralized in NPD keyword network. On the other hand, as a result of examining the change of preferential attachment of keywords over the time, we suggested the required new research direction including i) NPD collaboration with suppliers, ii) NPD considering market uncertainty, iii) NPD considering convergence with the other academic areas like technology management and knowledge management, iv) NPD from SME(Small and medium enterprises) perspective. The results of this study can be used to determine the research trends of NPD and the new research themes for interdisciplinary studies with other disciplines.

Provisioning Anonymous Communication in Ad Hoc Networks (Ad Hoc 네트워크상에서 익명성을 보장하는 방법에 관한 연구)

  • Kang, Seung-Seok
    • Journal of the Korea Society for Simulation
    • /
    • v.15 no.1
    • /
    • pp.77-85
    • /
    • 2006
  • The cost of downloading content from the Internet may be costly for mobile device users using its 3G connection, because the 3G connection cost to download data from the Internet is a function of the amount of data downloaded. This paper introduces an approach in which mobile devices, called peers, form an ad hoc network and share their downloaded content with others. As an example, spectators may want to collect/share information about players and game records in a stadium. In an art gallery, visitors may want to retrieve some background information about the displayed work from the nearby ad hoc network. In an outdoor class, a teacher may download today's topic files from the Internet, and all students may share the content with minimal or no cost paid. This is possible if mobile device has both a 3G interface and a wireless LAN interface. If the peers want to improve privacy md discourage traffic analysis when sharing content, this paper describes a low-delay anonymous connection between the sending peer and the receiving peer using two additional peers. Simulation results show that the transmission time overhead of the anonymous connection may increase 50% or less as the number of peers increase or the peers are scattered over the larger area.

  • PDF

The Prediction of the Helpfulness of Online Review Based on Review Content Using an Explainable Graph Neural Network (설명가능한 그래프 신경망을 활용한 리뷰 콘텐츠 기반의 유용성 예측모형)

  • Eunmi Kim;Yao Ziyan;Taeho Hong
    • Journal of Intelligence and Information Systems
    • /
    • v.29 no.4
    • /
    • pp.309-323
    • /
    • 2023
  • As the role of online reviews has become increasingly crucial, numerous studies have been conducted to utilize helpful reviews. Helpful reviews, perceived by customers, have been verified in various research studies to be influenced by factors such as ratings, review length, review content, and so on. The determination of a review's helpfulness is generally based on the number of 'helpful' votes from consumers, with more 'helpful' votes considered to have a more significant impact on consumers' purchasing decisions. However, recently written reviews that have not been exposed to many customers may have relatively few 'helpful' votes and may lack 'helpful' votes altogether due to a lack of participation. Therefore, rather than relying on the number of 'helpful' votes to assess the helpfulness of reviews, we aim to classify them based on review content. In addition, the text of the review emerges as the most influential factor in review helpfulness. This study employs text mining techniques, including topic modeling and sentiment analysis, to analyze the diverse impacts of content and emotions embedded in the review text. In this study, we propose a review helpfulness prediction model based on review content, utilizing movie reviews from IMDb, a global movie information site. We construct a review helpfulness prediction model by using an explainable Graph Neural Network (GNN), while addressing the interpretability limitations of the machine learning model. The explainable graph neural network is expected to provide more reliable information about helpful or non-helpful reviews as it can identify connections between reviews.

Analysis of Trends in Education Policy of STEAM Using Text Mining: Comparative Analysis of Ministry of Education's Documents, Articles, and Abstract of Researches from 2009 to 2020 (텍스트 마이닝을 활용한 융합인재교육정책 동향 분석 -2009년~2020년 교육부보도, 언론보도, 학술지 초록 비교분석-)

  • You, Jungmin;Kim, Sung-Won
    • Journal of The Korean Association For Science Education
    • /
    • v.41 no.6
    • /
    • pp.455-470
    • /
    • 2021
  • This study examines the trend changes in keywords and topics of STEAM education from 2009 to 2020 to derive future development direction and education implications. Among the collected data, 42 cases of Ministry of Education's documents, 1,534 cases of articles, and 880 cases of abstract of researches were selected as research subjects. Keyword analysis, keyword network and topic modeling were performed for each stage of STEAM education policy through the Python program. As a result of the analysis, according to the STEAM education policy stage, there were differences in the frequency and network of keywords related to STEAM education by media. It was confirmed that there was a difference in interest in STEAM education policy as there were differences in keywords and topics that were mainly used importantly by media. Most of the topics of the Ministry of Education's documents were found to correspond to topics derived from articles. The implications for the development direction of STEAM education derived from the results of this study are as follows: first, STEAM education needs to consider ways to connect multiple topics, including the humanities. Second, since the media has a difference in interest in STEAM education policy, it is necessary to seek a cooperative development direction through understanding this. Third, the Ministry of Education's support for core competency reinforcement and convergence literacy for nurturing future talents, the goal of STEAM education, and the media's efforts to increase the public's understanding of STEAM education are required. Lastly, it is necessary to continuously analyze the themes that will appear in the evaluation process and change STEAM education policy.

The Study on Data Governance Research Trends Based on Text Mining: Based on the publication of Korean academic journals from 2009 to 2021 (텍스트 마이닝을 활용한 데이터 거버넌스 연구 동향 분석: 2009년~2021년 국내 학술지 논문을 중심으로)

  • Jeong, Sun-Kyeong
    • Journal of Digital Convergence
    • /
    • v.20 no.4
    • /
    • pp.133-145
    • /
    • 2022
  • As a result of the study, the poorest keywords were information, big data, management, policy, government, law, and smart. In addition, as a result of network analysis, related research was being conducted on topics such as data industry policy, data governance performance, defense, governance, and data public. The four topics derived through topic modeling were "DG policy," "DG platform," "DG in laws," and "DG implementation," of which research related to "DG platform" showed an increasing trend, and "DG implementation" tended to shrink. This study comprehensively summarized data governance-related studies. Data governance needs to expand research areas from various perspectives and related fields such as data management and data integration policies at the organizational level, and related technologies. In the future, we can expand the analysis targets for overseas data governance and expect follow-up studies on research directions and policy directions in industries that require data-based future industries such as Industry 4.0, artificial intelligence, and Metaverse.

Why Are People Wearing Masks When They Are Relieved of Their Obligation? -Choosing Under Uncertainty by News Big Data Analysis (착용 의무 해제에도 마스크를 쓰는 이유 -뉴스 빅데이터 분석으로 확인한 불확실성하의 선택)

  • Ki-Ryang Seo;SangKhee Lee
    • The Journal of the Convergence on Culture Technology
    • /
    • v.9 no.4
    • /
    • pp.113-119
    • /
    • 2023
  • Despite the lifting of the mandatory wearing of masks, which was the main tool of the COVID-19 quarantine policy, we paid attention to the fact that some people are still wearing masks, and we wanted to clarify why people do not take off their masks. Through a survey in this regard, we were able to ascertain why some people continue to wear masks in a broader context. In this article, we directly and indirectly confirm the hidden side of citizens' continued wearing of masks by analyzing how the lifting of the mask-wearing obligation was reported in media articles that have a significant impact on citizens' behavior and attitude. Through this, it was confirmed that citizens continue to wear masks to protect themselves in an uncertain situation where the COVID-19 endemic has not been declared, despite the quarantine authorities' announcement of lifting the mandatory wearing. In a situation where crises such as COVID-19 are expected to repeat frequently in the future, it was concluded that it is important to build trust in the quarantine authorities.

Korean Customer Attitudes Towards SNS Shopping

  • Cho, Young-Sang;Heo, Jeong-Yoon;Youn, Myoung-Kil
    • Journal of Distribution Science
    • /
    • v.10 no.8
    • /
    • pp.7-14
    • /
    • 2012
  • As a new format of retailing, social shopping on SNS has rapidly grown in recent. Although there is much literature associated with customer behaviours in the academic world, little attention has been paid to identifying the shopping patterns of SNS shoppers. This paper will, thus, identify how perceived value has an impact on the buying intention of SNS shoppers, after illustrating what kind of factor influences the formation process of perceived value in the Korean marketplace. Given that SNS shoppers are for the most part 20s as well as 30s, the authors handed out questionnaires to them. Furthermore, based on literature review results, the conceptualised research model was developed. Despite lack of literature, the authors developed five constructs like price reduction, quantity- and time-limited message, product ranges, information-sharing, and required number of shoppers. The researchers made a considerable effort to identify the relationship between research concepts and each variable, based on a few research analysis methods such as frequency analysis, the Varimax rotation technique used orthogonal rotation, Cronbach's Alpha, PCA (Principle Component Analysis), and the like. Amongst the 5 variables used to measure the degree of influences on the perceived value as a social shopping characteristic, it has been evident that price cut, required minimum shoppers, product variety, and information-sharing have a positive impact on the perceived value formation processes of SNS customers. Also, this research implies that SNS retailers can differentiate themselves from other retailers by differently using the above factors. From a practitioner's point of view, these factors should be strategically used to increase the social shopping opportunities of SNS users. It is, furthermore, evident that the perceived value formed by the above 4 factors have played an important role in the buying decision process of SNS customers. In a sense, whether customers are aware of higher price cut rates, information-sharing, required minimum shoppers, and product variety has a positive impact on making buying decisions. From a retailer's point of view, online shopping mall operators are able to use blog as well as twitter to improve the buying intention as a marketing tool of social network, because the business activities provided by social shopping retailers, like the rapid, accurate responses to customer requirements, the provision of a variety of information, and the communications between customers are closely related to buying intentions. There are a few research limitations to conduct this empirical research. It was not easy to review prior papers, due to its lack. In spite of the increasing number of SNS shoppers in Korea, little research attention has been paid to this kind of research topic by academicians, because buying products or services through SNS is in its infancy. With regard to research populations, it would be difficult to generalise the research findings in Korea, owing to unbalanced respondent distribution. Considering the above research limitations as well as the growth of social shopping, many authors should pay considerable attention to SNS-related issues in the future, and develop the more sophisticated criteria to measure the characteristics of SNS shoppers.

  • PDF

The Context and Reality of Memes as Information Resources: Focused on Analysis of Research Trends in South Korea (정보자원으로서 '밈'의 맥락과 실재 - 국내 연구동향 분석을 중심으로 -)

  • Soram Hong
    • Journal of the Korean BIBLIA Society for library and Information Science
    • /
    • v.34 no.3
    • /
    • pp.227-253
    • /
    • 2023
  • The study is a preliminary study to conceptualize memes as information resources for literacy education in information environment changed with digital revolution. The study is to explain the context and reality of memes in order to promote the utilization of memes as information resources. The research questions are as follows: First, what topics are 'memes' studied with? Second, what things are captured and studied as 'memes'? The study conducted frequency and co-occurrence network analysis on 145 domestic studies and contents analysis on 73 domestic studies. The results are as follows: First, memes were mainly studied in the fields of 'humanities', 'social sciences', 'interdiciplinary studies', and 'arts and kinesiology'. Studies based on Dawkins' concept of memes (around 2012), studies on introducing the concept of memes to explain the spread of Korean Wave content (around 2015), and independent studies of memes as a major research topic in cultural sociology (around 2019) were performed. Second, memes are linguistic. Language memes (L-memes) are 102 (37%), language-visual memes (LV-memes) are 23 (8%), language-visual-musical memes (LVM-memes) are 21 (8%). Keyword 'language meme' ranked high in frequency, degree centrality and betweenness centrality of co-occurrence network. In other words, memes are expanding as a unique information phenomenon of cultural sociology based on linguistic characteristics. It is necessary to conceptualize meme literacy in terms of information literacy.