The Study on the Research Trend of Social Network Analysis and the its Applicability to Information Science

김성희,; 장로사,

doi:10.3743/kosim.2010.27.4.071

Cited by 14 publications

(6 citation statements)

References 1 publication

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“…It is represented by a line in the network. Density, centrality and centralisation are the most widely used indices in network analyses (Kim, 2011;Kim and Chang, 2010). Centrality describes the extent to which a node is located centrally in the entire network.…”

Section: Social Network Analysismentioning

confidence: 99%

Social network analysis of the Korean disaster-safety industry

Kim

Park

Chung

2018

DPM

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Natural disasters and social disasters have been causing more human losses and economic damages over the years. In the modern society, the government alone cannot fully manage disasters, because the number and size of disasters are increasing. Naturally, the role of the private sector in disaster management becomes more important, but there is a lack of studies about the disaster-safety industry.It is need to understand the market of disaster-safety industry to support and grow it. To analyze and understand the current state of the Korean disaster-safety industry, this study adopted the social network analysis technique. The social network analysis is an analysis method to describe the characteristics of the social network, and by using it, the complex industrial networks can be deeply understood.To collect data, semi-structured interviews were conducted on the K-SAFETY EXPO 2016. The By the analysis, it is found that the industrial/construction safety, disaster prevention, and traffic safety are major subdivisions of the disaster-safety industry. 47% of the companies are engaged in multiple industries, and 39% of the companies are engaged only in the disaster-safety industry. Companies in the industrial/construction safety subdivision have the widest range of market in terms of industrial distribution of their clients, and the average client number is high in the industrial/construction safety and the disaster prevention subdivisions. Overall, the public institutes are the most important client type of the overall disaster-safety industry. The disaster prevention subdivision shows a trend that its market is highly relying on their clients by the public institutes. It is also considered that high-value-added service industries and high-tech industry in the disaster-safety industry can widen the possible markets.This study analyzed the current state of the Korean disaster-safety industry, and found that the current disaster-safety industry market tends to highly depend on the demand of public institutions, therefore, the government-centered policy for growth of the disaster-safety industry is needed. It is also found that there are few transactions between the disaster-safety industry and service industry, so it is needed to study the required role of the disaster-safety industry by the service industry.

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Section: Social Network Analysismentioning

confidence: 99%

Social network analysis of the Korean disaster-safety industry

Kim

Park

Chung

2018

DPM

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“…This methodology can introduce research that represents a defined scope and identifies the most impactful study in the scope of the field. The rapid growth of research using social network analysis in the early 2000s demonstrated this application embedded in bibliometrics and webmetrics [39]. The study of research trends using a keyword network analysis was used to understand literature in the huge quantitative scale.…”

Section: Discussionmentioning

confidence: 99%

Sleep and Actigraphy Research Trends: A Bibliometric and Keyword Network Analysis From 2004 to 2020

Park¹,

Aini²

2021

Sleep Med Res

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Background and ObjectiveaaAs sleep is a predictor of quality of life, studying sleep health and measurement is important. Actigraphy as a physiologic measure based on monitoring an individual's movement has also been increasing in use as it has several advantages over traditional self-reports. This study aimed to report the research trends of sleep and actigraphy using a bibliometric and keyword analysis. MethodsaaUsing topic search queries, this study collected data from 3955 publications published between 2004 and 2020 and listed in the Web of Science Core Collection. A text-mining unstructured data analysis was performed using author keywords and a bibliographic analysis. ResultsaaStudies on sleep and actigraphy have been actively conducted in the fields of neurosciences and neurology but not in other fields. A gradual increase in publication and the steep increase in citations related to this topic occurring during the period considered. By clustering the author keywords, the analysis revealed five clusters: 1) monitoring physical activity and blood pressure, 2) measuring sleep quality, 3) insomnia and cognitive behavioral therapy for adolescents and children, 4) disorders and circadian rhythms, and 5) shift work. The leading research cluster has changed over the time. ConclusionsaaWith the increase in the number of studies and citations on sleep and actigraphy over the past 16 years, the trend of sleep and actigraphy studies have shifted from a focus on sleeprelated psychiatric disorders to a focus on cognitive behavioral therapy for children and adolescents and, more recently, the measurement of sleep quality.

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“…One of the reasons for this rise is that this application domain offers a particularly fertile place to test and develop advanced computational techniques to extract valuable information from networks. SNA has been widely used in diverse fields such as economic geography (Ter Wal and Boschma, 2009), information science (Kim and Chang, 2010) and social psychology (Wölfer and Hewstone, 2017). With the development of social network theory, SNA has also been gradually introduced into the domain of safety assessment to analyze the relevance of risk factors from the perspective of relational embedding.…”

Section: Literature Reviewmentioning

confidence: 99%

Forecasting law enforcement frequency of internet+ coal mine safety supervision

Long

Yang

et al. 2023

IJESM

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Purpose Coal is the basic energy and essential resource in China, which is crucial to the economic lifeline and energy security of the country. Coal mining has been ever exposed to potential safety risks owing to the complex geologic environment. Effective safety supervision is a vital guarantee for safe production in coal mines. This paper aims to explore the impacts of the internet+ coal mine safety supervision (CMSS) mode that is being emerged in China. Design/methodology/approach In this study, the key factors influencing CMSS are identified by social network analysis. They are used to develop a multiple linear regression model of law enforcement frequency for conventional CMSS mode, which is then modified by an analytical hierarchy process to predict the law enforcement frequency of internet+ CMSS mode. Findings The regression model demonstrated high accuracy and reliability in predicting law enforcement frequency. Comparative analysis revealed that the law enforcement frequency in the internet+ mode was approximately 40% lower than the conventional mode. This reduction suggests a potential improvement in cost-efficiency, and the difference is expected to become even more significant with an increase in law enforcement frequency. Originality/value To the best of the authors’ knowledge, this is one of the few available pieces of research which explore the cost-efficiency of CMSS by forecasting law enforcement frequency. The study results provide a theoretical basis for promoting the internet+ CMSS mode to realize the healthy and sustainable development of the coal mining industry.

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The Study on the Research Trend of Social Network Analysis and the its Applicability to Information Science

Cited by 14 publications

References 1 publication

Social network analysis of the Korean disaster-safety industry

Social network analysis of the Korean disaster-safety industry

Sleep and Actigraphy Research Trends: A Bibliometric and Keyword Network Analysis From 2004 to 2020

Forecasting law enforcement frequency of internet+ coal mine safety supervision

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