• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.1-17
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• 2014

The proliferation of using social media and social networking services affects the lifestyles of people. These phenomena are useful to companies that wish to promote and advertise new products or services through these social media; these social media venues also come with large amounts of user data. However, studies that analyze the data of social media within the perspective of information exchanges are hard to find. Much of the previous research in this area is focused on measuring the performance of exhibitions using general statistical approaches and piecemeal measures. Therefore, in this study, we want to analyze the characteristics of information exchanges in social media by using Twitter data sets, which are relating to the Mobile World Congress (MWC). Using this methodology provides exhibition organizers and exhibitors to objectively estimate the effect of social media, and establish strategies with social media use. Through a user network analysis, we additionally found that social attributes are as important as the popular attribute regarding the sustainability of information exchanges. Consequently, this research provides a network analysis using the data derived from the use of social media to communicate information regarding the MWC exhibition, and reveals the significance of social attributes such as the degree and the betweenness centrality regarding the sustainability of information exchanges.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.163-170
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• 2021

As a big data is being used in various industries, big data market is expanding from hardware to infrastructure software to service software. Especially it is expanding into a huge platform market that provides applications for holistic and intuitive visualizations such as big data meaning interpretation understandability, and analysis results. Demand for big data extraction and analysis using social media such as SNS is very active not only for companies but also for individuals. However despite such high demand for the collection and analysis of social media data for user trend analysis and marketing, there is a lack of research to address the difficulty of dynamic interlocking and the complexity of building and operating software platforms due to the heterogeneity of various social media service interfaces. In this paper, we propose a method for developing a framework to operate the process from collection to extraction and classification of social media data. The proposed framework solves the problem of heterogeneous social media data collection channels through adapter patterns, and improves the accuracy of social topic extraction and classification through semantic association-based extraction techniques and topic association-based classification techniques.

• The Research Journal of the Costume Culture
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• v.29 no.5
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• pp.694-705
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• 2021

Forming perceptions and having experiences through digital media is becoming more common than having in-person relationships in digital media environment. This study, which was conducted when Fashion Week transitioned to a digital platform in 2020, focuses on fashion shows that are announced through social media. The purpose of the study is to explore how traditional fashion media change through social media and what their media characteristics are from the perspective of remediation, which has been suggested by Bolter and Grusin (1999) as the logic of change in the new media. The results of the case analysis in this study, based on the definition and logic of remediation outlined through a literature review, are that social media fashion shows are remediated from traditional fashion shows in the manner that they are represented, improved, refashioned, and absorbed. The characteristics of remediation expressed in social-media-based fashion shows were derived from repurposed video content, improved the elements of fashion shows to express the shows in various ways, expanded places within the fashion shows, and decontextualized and visually flattened spatial discontinuity, and from genre transitions and perceptual shifts. Social-media-based fashion shows are becoming a tool to renew the fashion experience and views of fashion and strengthen the authenticity of the brand by interacting with the audience, improving on the spatial limitations of traditional fashion shows, and diversifying fashion presentation methods.

• The Journal of Information Systems
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• v.28 no.4
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• pp.293-311
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• 2019

Purpose This paper is to make a meta-analysis of the relationship between the social media use and learning performance as well as its potential moderating variables to clarify the differences in research conclusions in existing literatures, and refine the situational and method factors that affect the relationship between them. Methodology Meta-analysis used in this study can combine the quantitative data from different empirical studies, focus on the same research problem, and finally reach a research conclusion. Findings The results show that social media use and learning performance have a moderating positive correlation. The moderating effect test of usage scenarios shows that social media types, usage groups, application platforms and discipline fields have moderating effects on the relationship between social media use and learning performance. The moderating effect test of the research method found that measurement models, data attributes and learning performance indicators also had moderating effects on the relationship between social media use and learning performance.

• Journal of Information Technology Services
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• v.16 no.3
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• pp.127-146
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• 2017

The convergence of e-commerce and social media have given rise to a social commerce of online group-buying. Social commerce of online group-buying is a subset of B2C (Business to Consumer) and uses social media for marketing to facilitate online buying of products and services. The social commerce of online group-buying offers new and popular products or services every day, and uses social media to bring together separated consumers. In these backgrounds, we think that personality trait associated with seeking new and popular products or services, and social influence from social media are likely to be related to intention to use in social commerce of online group-buying. This study aims to examine and analyze novelty seeking and social influence that influence intention to use in social commerce of online group-buying in China. Our research model, which included novelty seeking and social influence, was developed based on the technology acceptance model. A questionnaire survey was carried out for empirical analysis. The results of empirical analysis based on a sample of 218 users showed that novelty seeking has a significant positive impact on intention to use, and social influence has a significant positive impact on perceived usefulness. We suggested academic implications and practical implications based on our empirical research.

• Journal of Information Technology Applications and Management
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• v.27 no.6
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• pp.117-139
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• 2020

This research analyzes the factors that affect the consumers' participation of the internet-only banks, and suggests effective financial sales strategies and methods to attract more users. Through prior research review and interviews with experts, the factors affecting the consumers to sign up for the internet banks are identified. The actual user data from the internet banks are used for the analysis, providing more systematic and credible results. The research shows that social media buzz positively affects the user growth, proving Granger Causality relation of increasing social media buzz on K Bank increases K Bank users. The research also shows that marketing activities noticeably impacts K Bank's positive user growth. On the other hand, the event of Kakao Bank's grand opening shows negative effect. The results from the research validates the need for periodical monitoring process of social media buzz. Moreover, the research proves that the integrated analysis of social media buzz and marketing effect is also essential.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.358-368
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• 2022

Social media is a window for everyone, individuals, communities, and companies to spread ideas and promote trends and products. With these opportunities, challenges and problems related to security, privacy and rights arose. Also, the data accumulated from social media has become a fertile source for many analytics, inference, and experimentation with new technologies in the field of data science. In this chapter, emphasis will be given to methods of trend analysis, especially ensemble learning methods. Ensemble learning methods embrace the concept of cooperation between different learning methods rather than competition between them. Therefore, in this chapter, we will discuss the most important trends in ensemble learning and their applications in analysing social media data and anticipating the most important future trends.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.7
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• pp.101-108
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• 2019

In this research, I conducted a semantic network analysis centering on media articles on purchasing, revitalizing, and utilizing the former Busan branch of Hansung Bank, a modern architectural heritage. We sought the most efficient analysis elements for the analysis of the social arguments about preservation and utilization embedded in media articles. For this reason, Degree Centrality measures how many connections the word described in the media article has, and Betweenness Centrality measures the influence that controls the flow of information through correlation I examined. In addition, keyword that express the theme well examined the aggregation structure in each sub-network. In this research, in theoretical terms, it makes sense in that the social discussion embedded in the article of the mass media is grasped empirically through semantic network analysis of words. Methodological aspect is best when it includes nouns and adjectives and the distance between words is more than four words in the analysis of the cohesive structure of the semantic network to determine whether the influence of social discussions is best assessed through the connection between words to media articles.

• Journal of the Korean Society of Food Culture
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• v.38 no.4
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• pp.239-245
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• 2023

The objective of this study was to explore how different types of rewards affect customers' inclinations to engage in environmental activities promoted through restaurant social media platforms. In addition, we investigated the potential moderating role of customer level of participation within the social media community. A total of 202 valid responses obtained by distributing a self-administered survey among restaurant patrons were subjected to hierarchical regression analysis to examine relationships between variables. The findings underscored the significant influence of economic and social rewards on shaping customer intent to participate in environmental initiatives promoted within restaurant social media communities. Furthermore, the study revealed that the extent of customer participation within the social media community moderated the relationship between rewards and their likelihood to partake in environmentally conscious behaviors. These results have meaningful implications for restaurant managers seeking to promote environmental initiatives effectively through social media platforms and within their establishments.

• Journal of Digital Convergence
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• v.19 no.5
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• pp.215-227
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• 2021

This study empirically studied the factors affecting the intensity of use of mobile social media and fatigue. Theories for the research framework were based on the theory of planned behavior, the theory of private information protection, the theory of flow, and the theory of process incentives. As a result of data analysis, it was found that self-efficacy, user habits, and flow experience positively influence the intensity of mobile social media use. This study assumed that personal information protection issues negatively affect the intensity of mobile social media use, but have little influence on the use intensity. The intensity of media use had a positive effect on media fatigue. In other words, when the intensity of using mobile social media increased, the feeling of fatigue increased. The expected process incentives variable did not show a moderating effect between media use intensity and social media fatigue. The findings will have implications for social media-related companies and organizations that want to use social media tools for business and public services.