• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.143-149
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• 2022

Since patent documents contain detailed results of research and development technologies, many studies on various patent analysis methods for effective technology analysis have been conducted. In particular, research on quantitative patent analysis by statistics and machine learning algorithms has been actively conducted recently. The most used patent data in quantitative patent analysis is technology keywords. Most of the existing methods for analyzing the keyword data were models based on the Gaussian probability distribution with random variable on real space from negative infinity to positive infinity. In this paper, we propose a model using gamma probability distribution to analyze the frequency data of patent keywords that can theoretically have values from zero to positive infinity. In addition, in order to determine the regression equation of the gamma-based regression model, two-mode network is constructed to visualize the technological association between keywords. Practical patent data is collected and analyzed for performance evaluation between the proposed method and the existing Gaussian-based analysis models.

• The Journal of the Korea Contents Association
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• v.20 no.12
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• pp.23-35
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• 2020

This study aims to examine trends in the IoT field by collecting and analyzing domestic papers on IoT that will have a great impact across industries and society. The survey period for this study was from 2015 to 2019, and the domestic papers on the IoT were collected using Naver's Academic Information. We extracted the keywords with high frequency from the domestic papers collected by the period and performed the centrality analysis to identify the central keywords among the keywords with high frequency. In terms of keyword frequency, 'sensor' and 'security' from 2015 to 2017 appeared as the top keywords with high frequency. From 2017, 'car' and 'intelligence' appeared as the top keywords with high frequency. In terms of keyword centrality, 'security' and 'sensor' from 2015 to 2016 appeared as highly centralized keywords. From 2017, 'intelligence', 'car' and 'industrial revolution' appeared as highly centralized keywords.

• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.1-9
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• 2022

Today, artificial intelligence (AI) has emerged as a key driver of national competitiveness, but it is also causing unexpected side effects in society. This study intends to examine major social issues by collecting papers on AI targeting KCI journals in the field of social science. Therefore, we conducted keyword analysis of papers from 2016 to 2020. As a result of the analysis, the keywords for 'robot' and 'education' appeared the most, and the top six clusters (issues) were derived through the keyword network. The main issues are as follows: the background and/or basic concept of AI, AI education, side effects of AI, legal issues of AI-based creations, intention to use AI products/services, and AI ethics. The results of this study can be used to expand the discussion on the social aspects of AI and to find policy directions at the national level.

• International Commerce and Information Review
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• v.19 no.1
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• pp.23-42
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• 2017

International Commerce and Information Review has been playing an important role of disseminating the outstanding research results in the fields such as trade information and systems, e-trade, regional studies, e-commerce, service trade, trade laws since 1999. This paper aims to find the research trends and distinguished characteristics in the field of trade information by analyzing research keywords of the research papers published in this journal using a social network analysis method. Research keyword data collected from the homepage of the academic society were cleaned and transformed into the co-occurrence network data, which are suitable for social network analysis. NodeXL Pro was used to analyze and visualize the pre-processed data. Through clustering analysis, the most important subject fields or interests were identified as well as those which worked as intermediaries for interdisciplinary researches.

• The Journal of Industrial Distribution & Business
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• v.10 no.8
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• pp.17-24
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• 2019

Purpose - The purpose of this study is to find out research directions for distribution and fusion and complex field to many domestic and foreign researchers carrying out related academic research by confirming research trends in the Journal of Distribution Science (JDS). Research Design, Data, and Methodology - To do this, I used keywords from a total of 904 papers published in the JDS excluding 19 papers that were not presented with keywords among 923. The analysis utilized word clouding, topic modeling, and weighted frequency analysis using the R program. Results - As a result of word clouding analysis, customer satisfaction was the most utilized keyword. Topic modeling results were divided into ten topics such as distribution channels, communication, supply chain, brand, business, customer, comparative study, performance, KODISA journal, and trade. It is confirmed that only the service quality part is increased in the weighted frequency analysis result of applying to the year group. Conclusion - The results of this study confirm that the JDS has developed into various convergence and integration researches from the past studies limited to the field of distribution. However, JDS's identity is based on distribution. Therefore, it is also necessary to establish identity continuously through special editions of fields related to distribution.

• Journal of the Korean Regional Science Association
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• v.32 no.3
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• pp.29-43
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• 2016

The purpose of this study is to derive research subject that has been overlooked in previous studies and contribute to seek to the direction of research in rural development by analyzing the studies in the last 30 years on rural society. In this study, Social Network Analysis was used for identifying the changes in research themes and connection structure of keyword. The study shows that in the previous Roh Moo-Hyun's Administration from 1986 to 2000, the convergence of the research is not active. In terms of the connection structure of keyword, lots of keywords are connected to the 'Migration, IMF, Satisfaction, Green Tourism' but its form is not complicated. In the Roh Moo-Hyun's Administration from 2001 to 2007, the academic exchanges and convergence of keywords on rural development were promoted research. The connection structure of keyword was formed like a complex cluster associated with 'The Rural Elderly, Rural Tourism, Rural Development Policy, Urban-Rural Comparison'. Although some scholars who study 'Women's Studies, Tourism' formed the cluster, its form is still passive. Since 2008 until now, the keyword network of rural development research clustered densely and formed singly. It reveals that the convergence of research subjects has proceeded actively. And studies such as the 'Community, Participation, Social capital, Quality of life, Social networks, Alternative food movement' have begun.

• Journal of Korea Port Economic Association
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• v.32 no.1
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• pp.79-95
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• 2016

This study identifies themes and trends in maritime economics and logistics by examining 303 papers published in international journals from 2000 to 2014 using keyword network analysis. Network analysis can be used because the collected data follow Zipf's law and the power law. Utilizing the degree centrality and betweenness centrality, we find the important keywords in each five year period and determine the importance of shared keywords. To further explain keyword centralities, we invented a Delta-C algorithm to show the trends of keywords over time. We found that degree centrality is useful for identifying important research themes in each period because it is mainly concerned with the number of connections. On the other hands, betweenness centrality is useful to determine the unique themes that emerge in each of the specific periods.

• Journal of Korean Home Economics Education Association
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• v.35 no.1
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• pp.105-124
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• 2023

The purpose of this study was to identify the characteristics of the contents included in the curriculum and 382 syllabi of the department of home economics education of College of Education in Korea and analyze the correlation by detailed area through the keyword network method. In order to analyze the home economics education curriculum and 382 syllabuses of a total of 11 universities, the frequency of keyword occurrence was analyzed using the KrKwic program, also the degree of connection between keywords and various centrality scales were calculated and visualized. The results of this study were as follows. First, as a result of analyzing the entire syllabi, keywords representing various fields such as family, secondary school, clothing, food, consumer, and design appeared evenly, and keywords related to teaching methods such as 'method', 'practice', 'change', and 'principle' were appeared. Those keywords showed high degree of connection and centrality. Second, in the detailed sectoral analysis, core keywords for each area appeared, and each subject were found to reflect the core keywords of the academic base. This study contributes to the conversion of curriculum of the department of home economics education to future-oriented and convergent curriculum.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.139-155
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• 2016

The purpose of this study is to find the research identity of the Korea Intelligent Information Systems Society through the profiling methods and co-word analysis in the most recent three-year('2014~'2016) study to collect keyword. In order to understand the research identity for intelligence information system, we need that the relative position of the study will be to compare identity by collecting keyword and research methodology of The korea Society of Management Information Systems and Korea Association of Information Systems, as well as Korea Intelligent Information Systems Society for the similar. Also, Korea Intelligent Information Systems Society is focusing on the four research areas such as artificial intelligence/data mining, Intelligent Internet, knowledge management and optimization techniques. So, we analyze research trends with a representative journals for the focusing on the four research areas. A journal of the data-related will be investigated with the keyword and research methodology in Korean Society for Big Data Service and the Korean Journal of Big Data. Through this research, we will find to research trends with research keyword in recent years and compare against the study methodology and analysis tools. Finally, it is possible to know the position and orientation of the current research trends in Korea Intelligent Information Systems Society. As a result, this study revealed a study area that Korea Intelligent Information Systems Society only be pursued through a unique reveal its legitimacy and identity. So, this research can suggest future research areas to intelligent information systems specifically. Furthermore, we will predict convergence possibility of the similar research areas and Korea Intelligent Information Systems Society in overall ecosystem perspectives.

• The Korean Journal of Applied Statistics
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• v.33 no.1
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• pp.75-86
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• 2020

Hotel review data can extract various information that includes purchasing factors that lead to consumption, advantages, and disadvantages for hotels. In particular, the sentiment keyword of the review data helps consumers understand the pros and cons of hotels. However, it is not efficient for consumers to read a large number of reviews. Therefore, it is necessary to offer a summary review to customers. In this study, we suggest providing summary information on sentiment keywords association as well as a network of hotels based on sentiment keywords. Based on a sentiment keyword dictionary, the extracted sentiment keywords associations construct the hotel network through topological data analysis based mapper. This hotel network allows a consumer to find some hotels associated with specific sentiment keywords as well as recommends the same related hotels. This summary information provides users with a summarized emotional assessment of hotels and helps hotel marketing teams understand consumers' perceptions of their hotel.