• Journal of the Korean Society for information Management
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• v.38 no.4
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• pp.199-230
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• 2021

This study is to present an analysis and activation plan for the effect of reuse of research data through investigation of researchers and reuse data on reuse of research data. To this end, 178 copies were analyzed based on the distribution and collection of surveys targeting academic researchers in the field of social science in Korea who have experience in calculating new research results by reusing research data. As a result, 1) Most researchers acquire reuse data through systems such as data repositories, data management systems, and research data DBs, and mainly reuse analysis data produced through experiments and observations. In addition, despite being a researcher who successfully reused research data, the awareness of research data sharing was low and did not share it in the face of various problems. 2) The reliability and validity of 10 factors derived through literature review and factor analysis (academic usefulness, research efficiency, researcher concerns, data vulnerability, direct effort, indirect effort, suitability for reuse, data completeness, data usefulness, and social conditions) were verified. 3) As a result of correlation analysis, research efficiency, social conditions showed a quantitative correlation with research data reuse intention, researcher concerns, data vulnerability, and direct effort showed a negative correlation with research data reuse intention. As a result of regression analysis, all of these factors had a significant effect on the intention to reuse research data, and in the order of research efficiency, social conditions, direct efforts, researchers' concerns, and data vulnerability. Based on this, a plan to revitalize the reuse of research data was proposed.

• The Journal of Industrial Distribution & Business
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• v.9 no.1
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• pp.99-110
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• 2018

Purpose - The purpose of this study is to investigate the relationship among narcissism, usage motives, usage behaviors, satisfaction with and continuance intention to use fashion social media. Research design, data, methodology - A questionnaire survey was used to collect data after conducting a pilot test. Based on the reliability test of the preliminary questionnaire used for the pilot test, the questionnaire was revised. The final questionnaires were administered to 238 fashion social media users and 216 were used for the data analysis. To assess the validity of these measures, exploratory factor analysis and the confirmatory factor analysis were performed. Structural equation modeling analysis were employed for data analysis. Results - Five factors of the usage motivation of fashion social media were extracted: information-seeking, relationship-seeking, practicality-seeking, enjoyment-seeking and self-expression motives. The statistical analysis confirmed the influence of the narcissism tendency on all of the usage motives of fashion social media, three of the fashion social media usage motives influencing information diffusion behavior, and the influence of the information diffusion behavior on users' satisfaction and continuance intention to use fashion social media. Narcissism exerted the highest influences on self-expression motive followed by information-seeking, enjoyment-seeking, relationship-seeking and practicality-seeking motives in order. Factors affecting fashion information diffusion behaviors are practicality-seeking motive, self-expression motive, and relationship-seeking motive. The greater the diffusion of information, the higher the satisfaction with using fashion social media. The consumers with higher satisfaction intended to use fashion social media and share information more frequently. Conclusions - The results indicate that narcissism is an important factor in fashion social media usage motivation. The main motives for narcissistic people to spread information is for the practical purpose at the most, and then to express their personality and style, and to build relationship with others. The satisfaction through active information sharing behaviors seems to play a key role to lead high continuance intention of fashion social media. These implies that marketing strategies to satisfy consumers' narcissism and motives to use social media, and to stimulate the information diffusion behaviors can be used to meet their needs for higher satisfaction with fashion social media.

• The Journal of Industrial Distribution & Business
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• v.9 no.11
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• pp.25-38
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• 2018

Purpose - This study aimed to identify the sub-dimensions of fashion social media quality (information quality, social quality, service quality, system quality) and investigate how they affect purchase intention through fashion information use behavior (information acceptance, information diffusion). Research design, data, and methodology - Data collection was carried out twice for systematic verification of the research model. In the first data collection, the reliability and validity of research variables were verified through 238 respondents and questionnaires were revised and supplemented based on their responses. In March 2018, the final survey was conducted from 755 respondents the age of 20 to 49. Using SPSS 23.0, descriptive statistics, exploratory factor analysis, correlation analysis were performed. In order to test hypotheses, structural equational modeling technique was employed using AMOS 23.0. Results - First of all, fashion Social media quality consists of four factors including information quality, social quality, service quality and system quality. Second, fashion Social media information quality, social quality, and system quality were shown to have a positive(+) effect on information acceptance behavior, and social quality, service quality and system quality were shown to have a positive(+) effect on information diffusion behavior. It was also determined that the acceptance and diffusion behaviors of fashion information through fashion Social media had positive(+) influence on purchase intention. Conclusions - This study holds academic significance in its identification of the components of fashion Social media quality and for conducting an empirical analysis on the causal relationship between fashion information acceptance and diffusion behaviors, and purchase intention. The results of this study indicate that fashion involvement is the key factors in determining the quality of Social media, the acceptance of information through Social media, and, by extension, the purchase of fashion products. Practitioners in the fashion industry may use the findings of this study in order to build more effective Social media strategy.

• Journal of Information Technology Applications and Management
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• v.22 no.3
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• pp.83-103
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• 2015

The rapid development of internet technologies and social media over the last few years has generated a huge amount of unstructured text data, which contains a great deal of valuable information and issues. Therefore, text mining-extracting meaningful information from unstructured text data-has gained attention from many researchers in various fields. Topic analysis is a text mining application that is used to determine the main issues in a large volume of text documents. However, it is difficult to identify related issues or meaningful insights as the number of issues derived through topic analysis is too large. Furthermore, traditional issue-clustering methods can only be performed based on the co-occurrence frequency of issue keywords in many documents. Therefore, an association between issues that have a low co-occurrence frequency cannot be recognized using traditional issue-clustering methods, even if those issues are strongly related in other perspectives. Therefore, in this research, a methodology to reorganize social issues from a research and development (R&D) perspective using social network analysis is proposed. Using an R&D perspective lexicon, issues that consistently share the same R&D keywords can be further identified through social network analysis. In this study, the R&D keywords that are associated with a particular issue imply the key technology elements that are needed to solve a particular issue. Issue clustering can then be performed based on the analysis results. Furthermore, the relationship between issues that share the same R&D keywords can be reorganized more systematically, by grouping them into clusters according to the R&D perspective lexicon. We expect that our methodology will contribute to establishing efficient R&D investment policies at the national level by enhancing the reusability of R&D knowledge, based on issue clustering using the R&D perspective lexicon. In addition, business companies could also utilize the results by aligning the R&D with their business strategy plans, to help companies develop innovative products and new technologies that sustain innovative business models.

• The Journal of Industrial Distribution & Business
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• v.9 no.6
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• pp.25-35
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• 2018

Purpose - In this study, the importance of interpersonal relations in the workplace as well as its correlation to satisfaction of social workers were investigated. In addition, effects of organizational culture as well as its implications for human resource management in social welfare workers were outlined. Research design, data, and methodology - A questionnaire was conducted on job satisfaction measured by the Minnesota Job Satisfaction (MSQ) questionnaire. For reliability, the questionnaire was distributed and collected by the self - filling method. From the collected data, reliability analysis, validity analysis (exploratory factor analysis) and multiple regression analysis were used. Cronbach's alpha was used to measure the reliability of the measurement variables and validity analysis was conducted to see if the questionnaires had the same concept as well as SPSS 19.0. Results - The results showed that group culture, hierarchical culture, and rational culture had significant positive effects on job satisfaction. Developmental culture had no effect on the job satisfaction levels. Conclusions - It is important to maintain the hierarchy in order to improve the efficiency of social welfare organizations, but social welfare organizations must accept external opinions and actively listen to the opinions of the employees in the organization.

• Journal of IKEEE
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• v.20 no.3
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• pp.235-240
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• 2016

In this study, we use the data collected from Twitter, as an SNS(Social Networking Service), for service innovation. This data was collected and processed by Flume. The data set in May 2016 was 4,766 and 15,543 from company S and company X, respectively. We were able to figure out the emotional atmosphere of the two companies through the sentiment analysis(SA) and to find out about the vertical relationship through the bibliometric analysis(BA). Furthermore, we were able to grasp the horizontal relationship through the social network analysis(SNA). It was concluded that SNS was worth while to derive an innovative item.

• Human Ecology Research
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• v.53 no.3
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• pp.293-307
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• 2015

Social commerce has a large impact on the emergence of the concept of society and individual lives that is recognized as one of the most important business areas in the Internet environment. A marketing agency, Trend Monitor (http://www.trendmonitor.co.kr), conducted a survey on social commerce usage and satisfaction level; subsequently, we used survey result data from 221 adult males and females for our research sample. Data analyses were conducted by reliability test, confirmatory factor analysis, t -test or one-way analysis of variance, and structural equation model (SEM) with IMB SPSS ver. 21.0 and ver. AMOS ver. 21.0. This study focused on multi-dimensional consumer innovativeness and found three elements of acceptability, competence, and distribution. Empirical verification through SEM presented data that suggests the three consumer innovativeness factors have a direct positive effect on social commerce that causes factors to indirectly affect satisfaction levels. This study indicated that the main consumption patterns in modern society take advantage of social commerce and satisfaction by improving a market economy to promote restoration. First, this study considers consumer innovativeness to have three factors. Secondly, research results help to understand relations between consumer innovativeness, use and satisfaction with social commerce that can help the social commerce industry establish effective market strategies through consumer innovativeness. The conclusion discusses implications for academic research and marketing strategies.

• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.151-159
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• 2015

This article analyzes English abstracts of the articles published in Journal of the Korean Data & Information Science Society using text mining techniques. At first, term-document matrices are formed by various methods and then visualized by social network analysis. LDA (latent Dirichlet allocation) and CTM (correlated topic model) are also employed in order to extract topics from the abstracts. Performances of the topic models are compared via entropy for several numbers of topics and weighting methods to form term-document matrices.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.113-119
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• 2020

Numerous tourist-related data produced on the Internet contain not only simple tourist information but also diverse ideas and opinions from users. In order to derive meaningful information about tourist sites from such big data, the social network analysis of tourist keywords can identify the frequency of keywords and the relationship between keywords. Thus, it is possible to make recommendations more suitable for users by utilizing the clear recommendation criteria of tourist attractions and the relationship between tourist attractions. In this paper, a recommendation system was designed based on tourist site information through big data social network analysis. Based on user personality information, the types of tourism suitable for users are classified through deep learning and the network analysis among tourist keywords is conducted to identify the relationship between tourist attractions belonging to the type of tourism. Tour information for related tourist attractions shown on SNS and blogs will be recommended through tagging.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.68-74
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• 2023

The food industry has been hit hard since the first outbreak of COVID-19 in 2019. However, as of April 2022, social distancing has been resolved and the restaurant industry has gradually recovered, interest in restaurant start-ups is increasing. Therefore, in this paper, 'restaurant start-up' was cited as a key keyword through social media big data analysis using TexTom, and word frequency and cone analysis were conducted for big data analysis. The keyword collection period was selected from May 1, 2022, when social distancing due to COVID-19 was lifted, to May 23, 2023, and based on this, a plan to develop chatbot services for restaurant start-ups was proposed. This paper was prepared in consideration of what to consider when starting a restaurant and a chatbot service that allows prospective restaurant founders to receive information more conveniently. Based on these analysis results, we expected to contribute to the process of developing chatbots for prospective restaurant founders in the future