• 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.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.5
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• pp.1377-1393
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• 2023

Social media is used for various purposes including entertainment, communication, information search, and voicing their thoughts and concerns about a service, product, or issue. The social media data can be used for information mining and getting insights from it. The World Health Organization has listed COVID-19 as a global epidemic since 2020. People from every aspect of life as well as the entire health system have been severely impacted by this pandemic. Even now, after almost three years of the pandemic declaration, the fear caused by the COVID-19 virus leading to higher depression, stress, and anxiety levels has not been fully overcome. This has also triggered numerous kinds of discussions covering various aspects of the pandemic on the social media platforms. Among these aspects is the part focused on vaccines developed by different countries, their features and the advantages and disadvantages associated with each vaccine. Social media users often share their thoughts about vaccinations and vaccines. This data can be used to determine the popularity levels of vaccines, which can provide the producers with some insight for future decision making about their product. In this article, we used Twitter data for the vaccine popularity detection. We gathered data by scraping tweets about various vaccines from different countries. After that, various machine learning and deep learning models, i.e., naive bayes, decision tree, support vector machines, k-nearest neighbor, and deep neural network are used for sentiment analysis to determine the popularity of each vaccine. The results of experiments show that the proposed deep neural network model outperforms the other models by achieving 97.87% accuracy.

• Asian Journal for Public Opinion Research
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• v.5 no.1
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• pp.41-62
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• 2017

The political reformation in Indonesia is a determinant factor of the change in political communications and the roles of media. Currently, the political elites need media support, since it contextually has a significant role. Whoever has a good relationship with the media, will be loved by the public. On the other hand, the media also have a vested interest in the elite in running businesses and building the power of industry. Policies and capital pose a challenge to maintaining the continuity of the media. Independence and control of media are at stake, when the interests of the media and the elite collaborate with each other and then build a benefit on both sides. Meanwhile, the role of social media also cannot be neglected. The Indonesian political communication system is characterized by the presence of social media in a pseudo-relationship between the elite and the public. This paper tries to explain the growing trends of research in the academic environment and the research trends in political practice in Indonesia after the occurrence of post-reformation era in legislative and executive elections. The method used is the meta-analysis of research outcomes of university (dissertations) and secondary data sources. Data processing is done by meta-analysis of secondary data. The results of meta-analysis research indicate that, the objective conditions, in Indonesia, especially the political conditions, stimulate new spaces in communication research. The study of political communication becomes dominant in the academic environment. In addition, communication research is also characterized by a shift from the linear perspective (positivistic paradigm) to the interactive perspective (naturalistic paradigm). On the other hand, the development of politic and governance situations in Indonesia has prompted the establishment of polling agencies that help citizens understand the maps of political power and candidates in general elections and regional head elections.

• The Journal of the Korea Contents Association
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• v.15 no.4
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• pp.407-419
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• 2015

As the use of social media has gained mainstream popularity, concerns on the particulars of the users' motivation and method of use is on the rise. Under uses and gratifications approach, this study analyzes the use behaviors in Kakao-story, Facebook, and Twitter, and analyzes the changes in the perception of social support by the users of the media. Data was analyzed from 240 online questionnaire surveys. The study finds that the frequency of use of social media differs depending upon the personality of the users and their purpose of use, both of which also influence their type of use. It also finds that frequent use of social media increased the users' perception of social support, whereas their type of use had no effect with such perception. Communication behavior through social media seem to increase perception of social support.

• Journal of Information Technology Services
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• v.15 no.1
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• pp.97-111
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• 2016

In the creative economy paradigm, motivation of the opportunity based startup is a continuous concern to policy-makers. Recently, bigdata anlalytics challenge traditional methods by providing efficient ways to identify social trend and hidden issues in the public sector. In this study the authors introduce a case study using social bigdata analytics for conducting policy analysis. A semantic network analysis was employed using textual data from social media including online news, blog, and private bulletin board which create buzz on the startup business. Results indicates that each media has been forming different discourses regarding government's policy on the startup business. Furthermore, semantic network structures from private bulletin board reveal unexpected social burden that hiders opening a startup, which has not been found in the traditional survey nor experts interview. Based on these results, the authors found the feasibility of using social bigdata analysis for policy-making. Methodological and practical implications are discussed.

• Journal of Information Technology Applications and Management
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• v.30 no.5
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• pp.121-139
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• 2023

This study tried to identify factors affecting online activity before and after the COVID-19 pandemic. To this end, the effects of consumer innovativeness, self-esteem, and need for cognition on the activity of online media such as Internet and social media were investigated, and whether privacy concerns had a moderating effect. For this study, survey data from 2019(before the outbreak of COVID-19) to 2021(after the outbreak of COVID-19) of the 'Korea Media Panel Survey' surveyed by the Korea Information Society Development Institute was used for analysis. The research results that affect Internet activity are as follows. Before the outback of COVID-19, it was found that hedonic innovativeness and social innovativeness had a positive effect and cognitive innovativeness had a negative effect on increasing Internet activity. There was no moderating effect on privacy concerns. The period after the outbreak of COVID-19, need for cognition was found to have a positive effect on increasing social media activity. In addition, the moderating effect of privacy concerns was found in the relationship between need for cognition and Internet activity. There was no privacy concern effect before the outbreak of COVID-19, and the privacy concern effect appeared on functional innovation and need for cognition after the outbreak of COVID-19. This study aims to present various implications for companies to understand the characteristics of online consumers using the Internet and social media after the pandemic.

• Asia pacific journal of information systems
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• v.20 no.2
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• pp.103-124
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• 2010

Social communications using information and communication technologies (ICT) for social interactions have been making a significant impact on task performance in organizations. However, most of the existing studies on ICT (e.g., telephone and email) have only focused on technical improvement of communication efficiencies (e.g., information exchange and storage). In this paper, we claim that ICT may be another alternative source of knowledge creation that enables employees to work, find solutions, and achieve their goals faster and better. We investigate the impact of ICT in terms of both tasks and social aspects with knowledge creation as task performance. Also, we investigate the moderating effect of media synchronicity on these relationships. This study contributes to the understanding of contemporary communications media usage and its performance in organizations. We collected and analyzed survey data of 248 company employees, using PLS. The results indicate that task urgency and social influence directly affect ICT usage, and even knowledge creation. Also the media synchronicity moderates the relationship between the characteristics of a given task and ICT usage and the relationship between ICT usage and knowledge creation. Theoretical and practical implications of these findings are also discussed in the paper.

• International Journal of Computer Science & Network Security
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• v.21 no.12spc
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• pp.579-585
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• 2021

This study aims to provide an in-depth description of the practices of social media users in the Kingdom of Saudi Arabia (KSA)-specifically the users of Facebook and Snapchat-and the reasons for these practices, the decisions made, and the people involved. Qualitative methods were used to collect data in two rounds from 53 participants. The data analysis shows a clear preference for Snapchat over Facebook among the participants, as shown in their using the application many times daily and in the creation and use of new words derived from the application's name. On the other hand, one of the main reasons mentioned by the participants for not preferring Facebook was the unclear policy of security and privacy used in the application. This reason is important for all social media users, but, in particular, it is crucial for female users, as shown in the data. This is important for the designers and policymakers of the social media applications to understand and consider, as it would help them improve the current applications and create new ones.

• Journal of the Korean Society of Clothing and Textiles
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• v.40 no.4
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• pp.631-640
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• 2016

The youth-pursing syndrome is especially amplified through a variety of media due to medical technology development, increases in social activities, and influence. This study discusses the relationship of youth-pursuing, media appearance information interest, and media contact responses focused middle-aged women. Data were collected from 245 females aged 40-65 in Seoul, Daejeon and Chungbuk area residents. The SPSS WIN 21.0 program analyzed the data by descriptive statistics, factor analysis, and regression analysis. Youth-pursuing derived social, psychological, and outward factors. Only an outward factor of these three dimensions influenced a significant media appearance information interest, and media contact response. The regression analysis results for chronological age and cognitive age, cognitive age influenced all variables significantly (three factors of youth-pursuing, media appearance information interest, and media contact response). But chronological age influenced significantly only the media appearance information interest. This study verified the relationship of youth-pursuing and media variables (media appearance information interest and media contact response).