• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.7-14
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• 2022

COVID-19 has caused a global disturbance, increased anxiety, and panic, eliciting diverse reactions. While its cure has not been discovered, new infection cases and fatalities are being recorded daily. The focus of the present study was to analyze the reaction of gifted undergraduate students on social media during the quarantine period of the COVID-19. A special group of gifted students, who joined the program of attracting and nurturing talents at the University of Jeddah, University students as were the target sample of this study. To analyze online reactions during the pandemic; the choice of university students was arrived at as they are perceived to be gifted academically. Hence, the analysis of the impacts on their behavior on social media use is imperative. This study presented accurate and consistent data on the effects of social media using Twitter platforms on gifted students during the quarantine occasioned by the COVID-19 pandemic. The behavior of learners due to during the use of social media was extensively explored and results analyzed. The study was carried out between April and May 2020 (quarantine period in Saudi Arabia) to establish whether the online behavior of gifted students reflects positive or negative feelings. The methods used in conducting this study the research were online interviews and scraping participants' Twitter accounts (where most of the online activities and studies take place). The study employed the Activity theory to analyze the behavior of gifted students on social media. The sample size used was 60 students, and the analysis of their behavior was based on Activity theory Overall, the results showed proactive, positive behavior for coping with a challenging situation, educating society, and entertaining. Finally, this study recommends investing in gifted students due to their valuable problem-solving skills that can help handle global pandemics efficiently.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.114-116
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• 2012

According to common use of smart mobile devices, various services based on the location become to appear. Futhermore, as the number of social media users using the mobile devices grows rapidly, the needs for Social Media services based on location also increase. With proposing the method to access and analysis the location-based social media database by standard SNS API, this thesis introduces technical methods to generate and the information which users want to get and to service them by mobile in real time.

• Korean Journal of Computational Design and Engineering
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• v.20 no.3
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• pp.254-262
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• 2015

This study proposes an approach to Product Data Management (PDM) education for collaborative product data management, which can support collaborative product development process. This approach introduces social media and a PDM system into a framework for PDM education supported by consistent product development process and product data model. It has been applied to two PDM classes and the result shows that the social media in PDM education can support not only experiences of the collaborative product data management but also interactive and informal communications among instructors and participants using integrated social media with product data during courses.

• Journal of Contemporary Eastern Asia
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• v.12 no.2
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• pp.49-59
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• 2013

Social media such as Twitter and Facebook have become popular. In the age of social media, many people have become more active online. For example, about half of all global active Internet users are on Facebook (Perry 2012). Personal branding is a very important strategy to build on an individual's strengths, and this kind of branding is expected to contribute to self-actualization. Therefore, the presence of mentors who advise users to discover their own strong points for self-actualization is necessary. In this paper, we propose a personal branding support service, Mentors, which connects mentors and mentees. The core concept is: "Everyone has the face of both a mentor and mentee." The key function is sharing stages of self-analysis in human life design: Determining value, creating a mission, and forming a strategy. From this function, a good match between a mentor and mentee can be found. The program aims to improve human life by understanding the client's strengths and using social media effectively. Future work includes launching Mentors and evaluating its service.

• Journal of Smart Tourism
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• v.1 no.3
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• pp.21-29
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• 2021

This study explored the relationship between post types and linguistic characteristics in marketer-generated content and social media engagement to find the optimized content to enhance social media engagement level. Post data of 23,588 marketer-generated content were collected from 50 states' destination marketing organization Facebook pages in the United States. The collected data were analyzed by employing social media analytics, linguistic analysis, multivariate analysis of variance, and discriminant analysis. The results showed that there are significant differences in both engagement indicators and linguistic scores among the three post types. Based on research findings, this research not only provided researchers with theoretical implications but also suggested practitioners the most effective content designs for travel destination marketing in Facebook.

• 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 Information Technology Applications and Management
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• v.30 no.4
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• pp.65-76
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• 2023

On social media, companies create brand experiences while customers actively seek, consume, and generate brand-related content. Customer engagement plays a vital role in the marketing performance of social media-driven brands. This study explores the positive relationship between brand authenticity, aligning brand identity with image, and self-brand connection, aligning brand identity with consumers' self-concepts, on customer engagement and its subsequent impact on brand loyalty. The study surveyed 243 consumers engaged with brand-related social media content, validating hypotheses using structural equation modeling. Results confirmed that brand authenticity and self-brand connection positively affect customer engagement, which, in turn, boosts brand loyalty. These findings highlight the importance of companies enhancing brand authenticity and self-brand connection to drive customer engagement, with theoretical and practical implications provided.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.4
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• pp.35-45
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• 2018

Users are sharing many of contents such as text, image, video, and so on in SNS. There are various information as like as personal interesting, opinion, and relationship in social media contents. Therefore, many of recommendation systems or search systems are being developed through analysis of social media contents. In order to extract subject-related topics of social context being collected from social media channels in developing those system, it is necessary to develop ontologies for semantic analysis. However, it is difficult to develop formal ontology because social media contents have the characteristics of non-formal data. Therefore, we develop a social topic system based on semantic and subject correlation. First of all, an extracting system of social topic based on semantic relationship analyzes semantic correlation and then extracts topics expressing semantic information of corresponding social context. Because the possibility of developing formal ontology expressing fully semantic information of various areas is limited, we develop a self-extensible architecture of ontology for semantic correlation. And then, a classifier of social contents and feed back classifies equivalent subject's social contents and feedbacks for extracting social topics according semantic correlation. The result of analyzing social contents and feedbacks extracts subject keyword, and index by measuring the degree of association based on social topic's semantic correlation. Deep Learning is applied into the process of indexing for improving accuracy and performance of mapping analysis of subject's extracting and semantic correlation. We expect that proposed system provides customized contents for users as well as optimized searching results because of analyzing semantic and subject correlation.

• Genomics & Informatics
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• v.18 no.2
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• pp.17.1-17.4
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• 2020

The amount of content on social media platforms such as Twitter is expanding rapidly. Simultaneously, the lack of patient information seriously hinders the diagnosis and treatment of rare/intractable diseases. However, these patient communities are especially active on social media. Data from social media could serve as a source of patient-centric knowledge for these diseases complementary to the information collected in clinical settings and patient registries, and may also have potential for research use. To explore this question, we attempted to extract patient-centric knowledge from social media as a task for the 3-day Biomedical Linked Annotation Hackathon 6 (BLAH6). We selected amyotrophic lateral sclerosis and multiple sclerosis as use cases of rare and intractable diseases, respectively, and we extracted patient histories related to these health conditions from Twitter. Four diagnosed patients for each disease were selected. From the user timelines of these eight patients, we extracted tweets that might be related to health conditions. Based on our experiment, we show that our approach has considerable potential, although we identified problems that should be addressed in future attempts to mine information about rare/intractable diseases from Twitter.