• The Journal of the Korea Contents Association
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• v.21 no.9
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• pp.184-197
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• 2021

Prior to the establishment of 'Employment-Related Big Data Center (tentative name)' to support the development of customized employment services. This Paper examines the current status and limitation of employment-related data in korea. Then, the implications were derived through foreign employment-related big data construction cases. Through the above analysis, I proposed measures to build and utilize employment-related big data at the individual level, focusing on the Transitional Labour Markets theory that emphasizes the implementation of individual labor force states. Finally, we presented future challenges such as massive maintenance of employment-related DB, increased representation of big data to be built around employment insurance DB, and increased reliability of DB presented.

• The Journal of the Convergence on Culture Technology
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• v.5 no.4
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• pp.251-258
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• 2019

This study proposed a system that can improve the employment rate and maintenance employment rate by filtering information related to employment in analyzing big data for students who want to find employment. The subject was a two-year female university, the existing employment strategy participated in the job search with simple information such as school grades and personality. As a result, the maintenance employment rate was relatively low due to the decrease in the satisfaction of students seeking employment and the incompatibility with the post-employment aptitude. In order to solve these problems, we propose a system that determines and filters whether the input data in the process of analyzing big data such as employment-related information to improve employment and maintenance employment rates.

• The Journal of the Korea Contents Association
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• v.20 no.11
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• pp.110-118
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• 2020

Social media data serves as a proxy indicator to understand the problems and the future of public opinion in Korean society. This research used 109,015 news data from 2016 to 2018 to analyze the sensitivity of the elderly and employment in Korean society, and explored the possibility of expanding the labor force in Korean society, which is facing a cliff between the elderly and the population. Topic keywords for employment of the elderly include "elderly*employment", "elderly*employment", and "elderly*wage". As a result of the analysis, positive sensitivity prevails for most of the period, and it is possible to expand the working-age population. Positive feelings about expanding employment opportunities for the elderly and negative feelings about low wages have brought to light the reality of the elderly who are still poor despite their work. In this study, social big data was used to analyze the perceptions and sensibilities of Korean society related to the elderly and employment through hierarchical crowd analysis and related text mining analysis.

• Journal of Digital Convergence
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• v.17 no.1
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• pp.1-8
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• 2019

The purpose of this study is to analyze the employment trends of autonomous automobile industry which is related to the 4th Industrial Revolution. Previously, big data of the employment trends were divided into skill field and task field. As a result, if a company was employed in the field of skill field, it was required to have talent in which personality traits and innovation traits were prominent. Second, if the task field is a production worker, it is desirable to have talented person with outstanding personality traits. In addition, if the task field is management, it has been confirmed that communication qualities require outstanding talent. The results of this study suggest that it is possible to use the data as a basic data for finding an effective employment strategy by identifying the characteristics of the talented person and considering the suitability of the tendency of hiring.

• The Journal of Bigdata
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• v.2 no.2
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• pp.17-31
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• 2017

With the development of the big data environment, public institutions also have been providing big data infrastructures. Public data is one of the typical examples, and numerous applications using public data have been provided. One of the cases is related to the employment insurance. All employers have to make contracts for the employment insurance for all employees to protect the rights. However, there are abundant cases where employers avoid to buy insurances. To overcome these challenges, a data-driven approach is needed; however, there are lacks of methodologies to integrate, manage, and analyze the public data. In this paper, we propose a methodology to build a predictive model for identifying whether employers have made the contracts of employment insurance based on public data. The methodology includes collection, integration, pre-processing, analysis of data and generating prediction models based on process mining and data mining techniques. Also, we verify the methodology with case studies.

• Journal of Service Research and Studies
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• v.8 no.1
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• pp.73-87
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• 2018

Countries around the world are preparing policies to promote service economy. Recently, as the fourth industrial revolution is accelerating, interest in the service industry is increasing. Korea's service industry is among the lowest among OECD countries in terms of employment, value-added and productivity, and it is time to explore new development strategies. The Korean government is establishing a service economic development strategy to promote employment and economic vitality. However, in the era of the 4th industrial revolution, the service industry is very important in that it has to be fused with the manufacturing industry. This study examines the service industry policy related to the 4th industrial revolution which the central government, local governments, and countries around the world are pursuing through literature review. The Big data analysis is used to determine the interest rate of the seven major service industries and core technologies for the fourth generation industrial revolution.

• Journal of the Korea Convergence Society
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• v.11 no.7
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• pp.251-257
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• 2020

This study comparatively analyzed the differences in the talented human resources perceived by enterprises and job seekers in terms of recruitment trends of companies related to the 4th Industrial Revolution, focusing on 16 factors. The analysis data was collected from enterprises and job seekers related to the 4th Industrial Revolution, and the analysis method was applied to a convergence research methodology that mixes social network analysis and variance analysis using big data type. As a result, several things were verified. First, large enterprises emphasized communication, and small enterprises emphasized competency and confidence. Second, in the manufacturing industry, enterprises emphasized confidence and competence, and job seekers emphasized spec and passion. Third, in the service industry, enterprises emphasized personality and competence, and job seekers emphasized spec and global. Fourth, there was a big difference in talented human resources between enterprises and job seekers according to manufacturing and service industries. Based on these results, we discussed the opening of employment information for enterprises to reduce the recognition mismatch in the talented human resources.

• Therapeutic Science for Rehabilitation
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• v.11 no.2
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• pp.63-76
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• 2022

Objective : The purpose of this study is to examine the relationship with employment of the disabled considering the severity and the type of disability. Methods : Data from the 4th data of the 2nd wave Panel Survey of Employment for the Disabled (PSED) by Korea Employment Agency for Persons with Disabilities (KEAD) were used. The odds ratio of employment in disability types according to severity of disability was calculated by logistic regression analysis. Results : When the related variables were adjusted, the employment of internal disability type was significantly lower than that of external disability type by 0.413(95% CI:0.271-0.629) times in the group with severe disability. On the other hand, in the group with less severe disability, internal disability was 0.475(95% CI:0.327-0.690) times lower than that of external disability (p=<.001). Conclusions : Employment may vary depending on the type of disability, even if the disability severity level is the same. It is necessary to prepare judgment criteria that can reduce the variation in employment by considering both the type and severity of the disability.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.1-10
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• 2021

This paper aimed to look at the awareness of foreign workers in social platforms by using text mining, one of the big data techniques and draw suggestions for foreign workers. To achieve this purpose, data collection was conducted with search keyword 'Foreign Worker' from Jan. 1, to Dec. 31, 2020, and frequency analysis, TF-IDF analysis, and degree centrality analysis and 100 parent keywords were drawn for comparison. Furthermore, Ucinet6.0 and Netdraw were used to analyze semantic networks, and through CONCOR analysis, data were clustered into the following eight groups: foreigner policy issue, regional community issue, business owner's perspective issue, employment issue, working environment issue, legal issue, immigration issue, and human rights issue. Based on such analyzed results, it identified national awareness of foreign workers and main issues and provided the basic data on policy proposals for foreign workers and related researches.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.548-557
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• 2021

The purpose of this study was to determine the statistical usefulness of using atypical text data collected from media that are easy to collect to overcoming limits of the existing data related to economic activities of disabled people. In addition, by performing semantic network analysis, major issues by period that could not be grasped by statistical analysis were also identified. As a result, semantic network analysis revealed that the initiative of the public sector, such as the central and local government bodies, was strongly shown. On the other hand, in the private purchase sector, it was also possible to confirm the consumption revitalization trend and changes in production activities in the recent issue of Covid-19. While the term "priority purchase" had a statistically significant relation with the other two terms "vocational rehabilitation" and "employment for the disabled". For the regression results, while the term "priority purchase" had a statistically significant association with the other two terms "vocational rehabilitation" and "employment for the disabled". Further, some statistical analyses reveal that keyword data taken from media channels can serve as an alternative indicator. Implications for issue detection in the field of welfare economy for the disabled is also discussed.