• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.391-406
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• 2015

Social media have emerged as new communication channels between consumers and companies that generate a large volume of unstructured text data. This social media content, which contains consumers' opinions and interests, is recognized as valuable material from which businesses can mine useful information; consequently, many researchers have reported on opinion-mining frameworks, methods, techniques, and tools for business intelligence over various industries. These studies sometimes focused on how to use opinion mining in business fields or emphasized methods of analyzing content to achieve results that are more accurate. They also considered how to visualize the results to ensure easier understanding. However, we found that such approaches are often technically complex and insufficiently user-friendly to help with business decisions and planning. Therefore, in this study we attempt to formulate a more comprehensive and practical methodology to conduct social media opinion mining and apply our methodology to a case study of the oldest instant noodle product in Korea. We also present graphical tools and visualized outputs that include volume and sentiment graphs, time-series graphs, a topic word cloud, a heat map, and a valence tree map with a classification. Our resources are from public-domain social media content such as blogs, forum messages, and news articles that we analyze with natural language processing, statistics, and graphics packages in the freeware R project environment. We believe our methodology and visualization outputs can provide a practical and reliable guide for immediate use, not just in the food industry but other industries as well.

• Journal of the Korean Society of Safety
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• v.31 no.6
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• pp.113-120
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• 2016

People use social media platforms such as Twitter to leave traces of their personal thoughts and opinions. In other words, social media platforms retain the emotions of the people as it is, and accurately understanding the emotions of the people through social media will be used as a significant index for disaster management. In this research, emotion type modeling method and emotional quotient quantification method will be proposed to understand the emotions present in social media platforms. Emotion types are primarily analyzed based on 3 major emotions of affirmation, caution, and observation. Then, in order to understand the public's emotional progress according to the progress of disaster or accident and government response in detail, negative emotions are broken down into anxiety, seriousness, sadness, and complaint to enhance the analysis. Ultimately, positive emotions are further broken down into 3 more emotions, and Russell emotion model was used as a reference to develop a model of 8 primary emotions in order to acquire an overall understanding of the public's emotions. Then, the emotional quotient of each emotion was quantified. Based on the results, overall emotional status of the public is monitored, and in the event of a disaster, the public's emotional fluctuation rate could be quantitatively observed.

• Korean Journal of Childcare and Education
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• v.14 no.6
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• pp.187-203
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• 2018

Objective: This study aimed to examine the mediating effect of mothers' parenting stress on the relationship between their self-differentiation and the tendency of addiction to social media. Methods: The participants in this study were two hundred and eight mothers with children aged 36 months or younger. Data were analyzed statistically using frequency, Pearson's correlation coefficients, and hierarchical multiple regression analysis. Results: The results of the present study are as follows. First, the mothers' self-differentiation was negatively associated with their parenting stress and social media addiction tendency. Second, both the total scores of the mothers' parenting stress and their distress were found to partially mediate the relationship between their self-differentiation and social media addiction tendency. However, the mothers' daily stress did not mediate the relationship between the variables. Conclusion/Implications: The findings of the current study have implications for developing ways of intervening in mothers' social media addiction tendency by reducing their parenting stress, particularly for mothers with low levels of self-differentiation.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.187-198
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• 2021

The objective of this study is to examine the direct and indirect influences of government's role, organizational commitment, and media exposure on the corporate social and environmental responsibility disclosure (CSERD) of 42 Indonesian state-owned enterprises (SOEs) with good corporate governance as the mediator. This study uses a quantitative approach with path analysis to test the hypothesis. The sample in this study was directors of 42 state-owned enterprises in Indonesia. The data was collected using a questionnaire with items assessed on a five-point Likert scale. This study finds that 1) the government's role, organizational commitment, and media exposure have direct influences on good corporate governance and corporate social responsibility disclosure; 2) the government's role and organizational commitment have significant influences on corporate social and environmental responsibility disclosure with the mediation of good corporate governance, indicating that government's role and the organizational commitment are factors affecting Indonesian state-owned enterprises; and 3) the media exposure through good corporate governance mediation does not have a significant effect on corporate social and environmental responsibility disclosure. This means that media exposure is only one of the tools for CSERD, while SOEs have no obligation to disclose CSER through website or printed media.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.6
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• pp.219-230
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• 2022

The goal of this research is to look into the relationship between social media marketing activities and brand attachment in the online marketing business, based on the indirect effect of perceived value and self-brand connections. For this reason, the study has used self-administered questionnaires to collect the data from 425 males from the major cities of Pakistan including Islamabad, Karachi, Lahore, and Sialkot. Furthermore, based on the PLS-SEM technique the empirical findings show that social media marketing activities positively affect perceived value, self-brand connections, and brand attachment. Perceived value has a significant positive impact on brand attachment and mediates the influence of social media marketing activities on brand attachment. In addition to this, self-brand connections have a positive effect on brand attachment, and self-brand connections mediate the relationship between them. Thus, firms employing social media marketing activities successfully in their branding build upon a positive perception of the brand in the customer's mind resulting in customer attachment with the brand. This study can assist the e-commerce managers and brand managers in building strong customer attachment via perceived value and self-brand connections.

• Asian Journal for Public Opinion Research
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• v.11 no.1
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• pp.4-30
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• 2023

Previous research has empirically demonstrated the negative effects of social media use on young people's psychological well-being. Unlike most previous studies that focused on either Facebook or Instagram, this study comparatively examined the differences in upward comparison and its effects on self-esteem, life satisfaction, and depression between Facebook and Instagram. An analysis of survey data from 641 Korean college students, who reportedly use these two social media more actively than any other age group, found that college students experience more upward comparisons on Instagram than on Facebook. Upward comparisons on both Facebook and Instagram increased by college students' age and weekly usage time. Upward comparisons on Instagram increased by the additional factors of gender (females more than males) and number of "followings." Subsequently, the effects of upward comparison on psychological well-being were found to differ by social media platform. Upward comparisons were found to negatively impact all determinants of psychological well-being only on Instagram, but not on Facebook. The differences in upward comparison and its impact on young users' psychological well-being found in this study were discussed in terms of the different functional characteristics of the two social media platforms, which provides direction for further research needed to establish guidelines for healthy social media use by young people.

• Journal of Distribution Science
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• v.22 no.1
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• pp.79-94
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• 2024

Purpose: The popularity of social media has altered how customers interact with businesses, and an increasing number of customers prefer to voice their complaints on social media. Bystanders can observe the customer complaint process on social media, but the impact of transparency on bystanders remains uncertain. Therefore, this study established and verified a model for defining the effect of transparency and service recovery types on bystanders. Research Design and Methodology: In this study, we used the internet survey platform "So Jump" to collect data. And we validated three studies with SPSS 26.0 and Smart PLS 4.0. Result: First, we showed that the transparency process (vs. result) is more likely to increase customer forgiveness and E-loyalty and reduce E-NWOM intention among bystanders. Second, customer forgiveness also plays a complementary mediating role between transparency and E-loyalty, as well as between transparency and E-NWOM intention. Finally, we found a modest interaction effect between transparency (process vs. result) and service recovery types (psychological vs. tangible vs. hybrid) on bystanders' customer forgiveness and E-loyalty. Conclusions: This study provides actionable recommendations for how service managers can effectively employ social media as a means for distributing feedback information to manage service recovery in the future.

• International Journal of Computer Science & Network Security
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• v.24 no.7
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• pp.207-213
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• 2024

This study investigated the perceived usability of the Blackboard learning management system (LMS) amongst students at Umm Al-Qura University. A quantitative approach was employed to explore the potential relationship between Blackboard usability and social media platform usage. Additionally, the study aimed to identify other factors influencing perceived usability. Data were collected through a three-section questionnaire distributed electronically to a sample of students (n=544). The findings, based on System Usability Scale (SUS) scores, revealed that the overall perceived usability of Blackboard resided near the midpoint of the scale, indicating an "acceptable" level. A potential negative correlation emerged between social media usage time and perceived Blackboard usability. Students who reported lower social media usage exhibited higher SUS scores. Training on Blackboard usage demonstrably exerted a positive influence on perceived usability. Gender was not identified as a statistically significant factor. An analysis of student support methods revealed that seeking help from a friend was the most prevalent approach, followed by search engines, university technical support, and social media platforms. The findings suggest that implementing strategies to improve Blackboard usability at Umm Al-Qura University could be achieved through readily accessible training materials and the exploration of alternative support channels.

• Journal of the Korea Fashion and Costume Design Association
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• v.22 no.3
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• pp.49-61
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• 2020

This study analyzed the social media accounts and performed a Big Data analysis of Z-generation fashion using Textom Text Mining Techniques program and Ucinet Big Data analysis program. The research results are as follows: First, as a result of keyword analysis on 67.646 Z-generation fashion social media posts over the last 5 years, 220,211 keywords were extracted. Among them, 67 major keywords were selected based on the frequency of co-occurrence being greater than more than 250 times. As the top keywords appearing over 1000 times, were the most influential as the number of nodes connected to 'Z generation' (29595 times) are overwhelmingly, and was followed by 'millennials'(18536 times), 'fashion'(17836 times), and 'generation'(13055 times), 'brand'(8325 times) and 'trend'(7310 times) Second, as a result of the analysis of Network Degree Centrality between the key keywords for the Z-generation, the number of nodes connected to the "Z-generation" (29595 times) is overwhelmingly large. Next, many 'millennial'(18536 times), 'fashion'(17836 times), 'generation'(13055 times), 'brand'(8325 times), 'trend'(7310 times), etc. appear. These texts are considered to be important factors in exploring the reaction of social media to the Z-generation. Third, through the analysis of CONCOR, text with the structural equivalence between major keywords for Gen Z fashion was rearranged and clustered. In addition, four clusters were derived by grouping through network semantic network visualization. Group 1 is 54 texts, 'Diverse Characteristics of Z-Generation Fashion Consumers', Group 2 is 7 Texts, 'Z-Generation's teenagers Fashion Powers', Group 3 is 8 Texts, 'Z-Generation's Celebrity Fashions' Interest and Fashion', Group 4 named 'Gucci', the most popular luxury fashion of the Z-generation as one text.