• Journal of Distribution Science
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• v.10 no.11
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• pp.5-10
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• 2012

Purpose - The purpose of this study is to investigate the impact of awareness on the characteristics of a consumers' social commerce. This study examines whether the characteristics of social commerce influence the purchase intentions in accommodating these types of social commerce. Research design, data, methodology - The data for the study were collected and analyzed from a sample of 126 adult customers, comprising both males and females, using social commerce. The survey was conducted and the results aggregated through distributing a copy to each participant. For statistical analysis of the data collected, SPSS 18.0 statistical package was used. Results - The results can be summarized as follows. First, the perceptions about the characteristics of Social Commerce demonstrated a significant effect for attitudes. Second, the attitudes demonstrated positive effects on purchase intention. Third, the subjective norm affected the purchase intention. Fourth, perceived behavioral control influenced the purchase intentions. Conclusions - As a result, perceptions about the characteristics of Social Commerce may be seen in the positive effects on purchase intention. Using social commerce in the future, retailers would need to increase the scope of the study, through applying more diverse characteristics of Social Commerce.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.146-147
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• 2017

Big data analysis is a technique for effectively analyzing unstructured data such as the Internet, social network services, web documents generated in the mobile environment, e-mail, and social data, as well as well formed structured data in a database. The most big data analysis techniques are data mining, machine learning, natural language processing, and pattern recognition, which were used in existing statistics and computer science. Global research institutes have identified analysis of big data as the most noteworthy new technology since 2011. Therefore, companies in most industries are making efforts to create new value through the application of big data. In this study, we analyzed using the Social Matrics which a big data analysis tool of Daum communications. We analyzed public perceptions of "Internet of things" keyword, one month as of october 8, 2017. The results of the big data analysis are as follows. First, the 1st related search keyword of the keyword of the "Internet of things" has been found to be technology (995). This study suggests theoretical implications based on the results.

• Journal of Contemporary Eastern Asia
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• v.14 no.2
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• pp.87-96
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• 2015

Social media comprises a vast and consequential landscape that has been poorly mapped and understood. Hundreds of millions of people have eagerly moved many of the conversations and discussions that compose civil society into these services and platforms. There is a need to document and analyze these social spaces for many academic and commercial purposes. The Social Media Research Foundation has engaged a strategy to cultivate better research into the structure and dynamics of social media. The foundation is dedicated to the creation of open tools, open data, and open scholarship related to social media. It has implemented a free and open network collection, analysis, and visualization tool called NodeXL to facilitate social media network research. Using NodeXL a group of researchers has collectively authored a publicly available archive, called the NodeXL Graph Gallery, composed of network data sets and visualizations from users around the world. This site has enabled the aggregation of tens of thousands of network datasets and images. Use of the archive has led to scholarly research results that are based on the wide range and scope of social media data sets available.

• Journal of Information Technology Services
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• v.17 no.3
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• pp.171-189
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• 2018

To remove software defects and improve performance of software, many developers perform code inspections and use static analysis tools. A code inspection is an activity that is performed manually to detect software defects in the developed source. However, there is no clear criterion which source codes are inspected. A static analysis tool can automatically detect software defects by analyzing the source codes without running the source codes. However, it has disadvantage that analyzes only the codes in the functions without analyzing the relations among source functions. The functions in the source codes are interconnected and formed a social network. Functions that occupy critical locations in a network can be important enough to affect the overall quality. Whereas, a static analysis tool merely suggests which functions were called several times. In this study, the core functions will be elicited by using social network analysis and DEA (Data Envelopment Analysis) for CUBRID open database sources. In addition, we will suggest clear criteria for selecting the target sources for code inspection and will suggest ways to find core functions to minimize defects and improve performance.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.4
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• pp.169-181
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• 2018

Under the constantly intensifying global competition environment, many companies are exploring new business opportunities in the field of social innovation using creating shared value. In seeking social innovation, it is a key starting point of social innovation to clarify the problem to be solved and to grasp the cause of the problem. Among the many problem solving methodologies, design thinking is getting the most attention recently in various fields. Design Thinking is a creative problem solving method which is used as a business innovation tool to empathize with human needs and find out the potential desires that the public does not know, and is actively used as a tool for social innovation to solve social problems. However, one of the difficulties experienced by many of the design thinking project participants is that it is difficult to analyze the observed data efficiently. When analyzing data only offline, it takes a long time to analyze a large amount of data, and it has a limit in processing unstructured data. This makes it difficult to find fundamental problems from the data collected through observation while performing design thinking. The purpose of this study is to integrate qualitative data analysis and quantitative data analysis methods in order to make the data analysis collected at the observation stage of the design thinking project for social innovation more scientific to complement the limit of the design thinking process. The integrated methodology presented in this study is expected to contribute to innovation performance through design thinking by providing practical guidelines and implications for design thinking implementers as a valuable tool for social innovation.

• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.3
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• pp.71-86
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• 2013

This research explores the question how interactions between customer and firm affect firm growth. To test suggested hypotheses, this study collects data on social commerce industry in Korea during the period from the beginning of social commerce industry in Korea, May 2010, to March 2012, and investigates the effect of social media on the growth of social commerce firms. We suggest two hypotheses in this study. First, as web traffic inflow through social media into a focal social commerce increases, the growth rate of the focal social commerce increases. Second, the more diverse social media channel through which web traffic inflows into a focal social commerce, the weaker the positive effect of web traffic inflow on the growth rate of the focal social commerce. Analysis of data shows that inflow through social media is positively related to the growth of social commerce. In addition, our analysis shows that inflow channel diversity weakens the positive relationship between web traffic inflow through social media and growth rate of social commerce firms. These results suggest that firms need to concentrate on few social media in order to attract customers. The study contributes to understanding how interaction between firms and customers influences the growth of the firm.

• Journal of the Korean housing association
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• v.27 no.6
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• pp.113-124
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• 2016

The purpose of this study is to analyze characteristics of rental housing management and service preference according to social relationship types. The data for the analysis was collected through questionnaire survey method from 12th, April to 4th, May, 2016 and 565 data were finally used. Data were statistically analyzed using SPSS WIN 18.0. The findings of this study are as follows: 1) the six factors on social relations of subjects are made up as 'interpersonal stress of the relationship', 'new relationship', 'neighbor relations', 'online relationship', 'family relations', and 'friendship'. 2) Along with this result, cluster analysis was carried out, and four social relation types are classified and named as the 'extroverted relationship type', 'passive relationship type', 'active relationship type' and 'introverted relationship type'. 3) Rental housing management and service was examined separately as 'housing management system', 'housing services', and 'community facilities'. Differences in preference were identified by type of social relationship. Housing services and community facilities showed a significant difference in almost all items. In the housing management system, most of the items did not show any significant difference according to social relationship types.

• Journal of Information Technology Services
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• v.14 no.2
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• pp.143-158
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• 2015

Companies and governments in an era of big data have been tried to create new values with their data resources. Among many data resources, many companies especially pay attention to data which is obtained from Social Network Service (SNS) because it reveals precise opinion of customers and can be used to estimate profiles of them from their social relationships. However, it is not only hard to collect, store, and analyze the data, but system applications are also insufficient. Therefore, this study proposes a S-POS (Social POS) system which consists of three parts; Twitter Side, POS Side and TPAS (Twitter&POS Analysis System). In this system, SNS data and POS data which are collected from Twitter Side and POS Side are stored in Mongo D/B. And it provides several services with POS terminal based on analysis and matching results which are generated from TPAS. Through S-POS system, we expect to efficient and effective store and sales managements of system users. Moreover, they can provide some differentiated services such as cross-selling and personalized recommendation services.

• International Journal of Advanced Culture Technology
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• v.6 no.2
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• pp.58-64
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• 2018

This main purpose of the study is to identify social network of communicators sharing information on Bokjiro for publicizing welfare policy. This study employs NodeXL pro to understand networks and their role in the social network. The data for social network analysis was collected from Twitter for a week. The result of the analysis shows that the social network of communicators on Bokjiro does not have many nodes. It also has an independent network with high possibility of information distortion. Little communicators have controlling power in information flow in one way of communication. According to the result, it is not effective for marketing strategy of welfare policy in providing online information through Bokjiro. The study suggests that the government should use the transactional approach to marketing based on agent-oriented activity focusing on the exchange relationship between information providers and demanders in an age of networked intelligence.

• The Journal of the Korea Contents Association
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• v.13 no.4
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• pp.73-85
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• 2013

This study examines the online social capital of local press using the website and social media. Moreover, the paper respectively visualizes web feature as Web 1.0 and social feature analysis as Web 2.0 by applying correspondence analysis. For data, the study analyzes 10 representative local press in Yeungnam areas. To collect the data, two coders coded web features from the websites and we employed NodeXL, an open-source software tool, for social media data. The results reveal that local websites expend online social capital using social media account. Especially, the social features of local presses attach importance to Twitter as the main press keep the well-balance use among all platforms.