• Journal of Electrical Engineering and Technology
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• v.11 no.1
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• pp.227-233
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• 2016

Google Trends provides weekly information on keyword search frequency on the Google search engine. Search volume patterns for the search keyword can also be analyzed based on category and by the location of those making the search. Also, Google provides “Hot searches” and “Top charts” including top and rising searches that include the search keyword. All this information is kept up to date, and allows trend comparisons by providing past weekly figures. In this study, we present a predictive model for TV markets using the searched data in Google search engine (Google Trend data). Using a predictive model for the market and analysis of the Google Trend data, we obtained an efficient and meaningful result for the TV market, and also determined highly ranked countries and cities. This method can provide very useful information for TV manufacturers and others.

• Journal of Wellbeing Management and Applied Psychology
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• v.5 no.4
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• pp.33-37
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• 2022

Purpose: This study aims to understand the trend and central concept of domestic researches on laughter therapy. For the analysis, this study used total 72 theses verified by inputting the keyword 'laughter therapy' from 2007 to 2021. Research design, data and methodology: This study performed the development and analysis of keyword co-occurrence network, analyzed the types of researches through topic modeling, and verified the visualized word cloud and sociogram. The keyword data that was cleaned through preprocessing, was analyzed in the method of centrality analysis and topic modeling through the 1-mode matrix conversion process by using the NetMiner (version 4.4) Program. Results: The keywords that most appeared for last 14 years were laughter therapy, depression, the elderly, and stress. The five topics analyzed in thesis data from 2007 to 2021 were therapy, cognitive behavior, quality of life, stress, and the elderly. Conclusions: This study understood the flow and trend of research topics of domestic laughter therapy for last 14 years, and there should be continuous researches on laughter therapy, which reflects the flow of time in the future.

• Journal of Information Technology Services
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• v.19 no.4
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• pp.49-61
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• 2020

Prior studies on technology predictions attempted to predict the emergence and spread of emerging technologies through the analysis of correlations and changes between data using objective data such as patents and research papers. Most of the previous studies predicted future technologies only from the viewpoint of technology development. Therefore, this study intends to conduct technical forecasting from the perspective of the consumer by using keyword search frequency of search portals such as NAVER before and after the introduction of emerging technologies. In this study, we analyzed healthcare technologies into three types : measurement technology, platform technology, and remote service technology. And for the keyword analysis on the healthcare, we converted the classification of technology perspective into the keyword classification of consumer perspective. (Blood pressure and blood sugar, healthcare diagnosis, appointment and prescription, and remote diagnosis and prescription) Naver Trend is used to analyze keyword trends from a consumer perspective. We also used the ARIMA model as a technology prediction model. Analyzing the search frequency (Naver trend) over 44 months, the final ARIMA models that can predict three types of healthcare technology keyword trends were estimated as "ARIMA (1,2,1) (1,0,0)", "ARIMA (0,1,0) (1,0,0)", "ARIMA (1,1,0) (0,0,0)". In addition, it was confirmed that the values predicted by the time series prediction model and the actual values for 44 months were moving in almost similar patterns in all intervals. Therefore, we can confirm that this time series prediction model for healthcare technology is very suitable.

• Convergence Security Journal
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• v.14 no.2
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• pp.35-41
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• 2014

With ubiquitous computing and network, the concern of government, business and academy for IT or ICT convergence has been increased. In this paper, through the analysis of keyword trend for ICT convergence services from 2000's mid, the efficient policy is proposed by estimating the understanding and concern of common people. In addition to, the concept and development step of convergence are analyzed, and the keyword analysis for the ICT convergence services defined in TTA is performed. The services are classified into smart home work transportation, Health ICT, RFID USN, M2M IoT, e-Navigation, intelligent robot, and the keywords for each service are analyzed. The analytic results indicate that the keyword trend varies in the time, and highly indexing keywords and new trend are defined. To provide the efficient ICT services, the new ICT convergence services needed for customer will be proposed with new IT technology development, IT standard, law management, and policy provisioining.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.151-158
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• 2019

This study aimed to analyze the research trend related on obesity in physical education in Korea through the keyword network analysis and to establish a basic database for effective design of prospective studies. To achieve it the study crawled co-occured keywords with 'obesity' and 'physical education' from RISS and analyzed the list from 1990 to 2018. They include 25 journal papers and 38 dissertations. The results are as follows. First, recent 30 years 63 papers published in Korea with 'Obesity' and 'Physical Education', and there were 144 related keywords. Second, analyzing journals which have 'Obesity' and 'Physical Education', co-occured keywords in 4 centrality were 24 keywords(student, Korea, prevention, effect, level, body, activation, actual condition, lesson, child, investigation, participation, book, cause, activity, normal, degree, nutrition, physical strength, weight, elementary, light, inquiry, health), and 37 keyword occurred in top 30. Lastly, by CONCOR analysis the result could be divided into 2 clusters. One consists of the object of obesity and its invervention, and the other consists of negative keywords of obesity and its preliminery dimenstion. Through the result, this study showed the research trend which involves the concept of obesity in physical education in Korea. Through the result, prospective obesity research in physical education in Korea would be promoted.

• Journal of Convergence for Information Technology
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• v.9 no.2
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• pp.7-16
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• 2019

The purpose of this study is to identify the characteristics of researches that have been conducted for the last 20 years through analyzing global research trends and evolutions of design articles from 1999 to 2018 with keyword network analysis. For this purpose, we selected 3,569 articles in 22 journals related to design research retrieved from the Scopus database and constructed keyword network model through the author keyword and index keyword. The frequency of the author and index keyword, the centrality of betweenness and degree were analyzed with the keyword network. The results show that design has been applied to various fields for recent 20 years, and the research trends of design could be quantitatively characterized by keyword network analysis. The result of this study could be used to suggest future research topics in the field of design based on quantitative and empirical data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.1996-2011
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• 2021

To understand a trend is to explore the intricate process of how something or a particular situation is constantly changing or developing in a certain direction. This exploration is about observing and describing an unknown field of knowledge, not testing theories or models with a preconceived hypothesis. The purpose is to gain knowledge we did not expect and to recognize the associations among the elements that were suspected or not. This generally requires examining a massive amount of data to find information that could be transformed into meaningful knowledge. That is, looking through the lens of big-data analytics with an inductive reasoning approach will help expand our understanding of the complex nature of a trend. The current study explored the trend of well-being in South Korea using big-data analytic techniques to discover hidden search patterns, associative rules, and keyword signals. Thereafter, a theory was developed based on inductive reasoning - namely the hook, upward push, and downward pull to elucidate a holistic picture of how big-data implications alongside social phenomena may have influenced the well-being trend.

• The KIPS Transactions:PartD
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• v.18D no.6
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• pp.501-508
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• 2011

A knowledge map, which has been recently applied in various fields, is discovering characteristics hidden in a large amount of information and showing a tangible output to understand the meaning of the discovery. In this paper, we suggested a knowledge map for research trend analysis based on keyword-relation networks which are constructed by using a database of the domestic journal articles in the computer engineering field from 2000 through 2010. From that knowledge map, we could infer influential changes of a research topic related a specific keyword through examining the change of sizes of the connected components to which the keyword belongs in the keyword-relation networks. In addition, we observed that the size of the largest connected component in the keyword-relation networks is relatively small and groups of high-similarity keyword pairs are clustered in them by comparison with the random networks. This implies that the research field corresponding to the largest connected component is not so huge and many small-scale topics included in it are highly clustered and loosely-connected to each other. our proposed knowledge map can be considered as a approach for the research trend analysis while it is impossible to obtain those results by conventional approaches such as analyzing the frequency of an individual keyword.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.4 no.1
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• pp.43-48
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• 2023

This study analyzed research trends in the field of ecological research. Data were collected based on a keyword search of the SCI, SSCI, and A&HCI databases from January 2002 to September 2022. The seven keywords, including biodiversity, ecology, ecotourism, species, climate change, ecosystem, restoration, wildlife, were recommended by ecological research experts. Word clouds were created for each of the searched keywords, and topic map analysis was performed. Topic map analysis using biodiversity, climate change, ecology, ecosystem, and restoration each generated 10 topics; topic maps analysis using the ecotourism keyword generated 5 topics; and topic map analysis using the wildlife keyword generated 4 topics. Each topic contained six keywords.

• International Journal of Advanced Culture Technology
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• v.12 no.2
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• pp.221-226
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• 2024

This study used text mining, a big data analysis technique, to explore XR trends in South Korea. For this research, I utilized a big data platform called BigKinds. I collected data focusing on the keyword 'XR', spanning approximately 14 years from 2010 to 2024. The gathered data underwent a cleansing process and was analyzed in three ways: keyword trend analysis, relational analysis, and word cloud. The analysis identified the emergence and most active discussion periods of XR, with XR devices and manufacturers emerging as key keywords.