• The korean journal of orthodontics
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• v.53 no.5
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• pp.328-335
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• 2023

Objective: The aim of this study was to determine whether an association between study quality, other study characteristics, and Altmetric Attention Scores (AASs) existed in orthodontic studies. Methods: The Scopus database was searched to identify orthodontic studies published between January 1, 2017, and December 31, 2019. Articles that satisfied the eligibility criteria were included in this study. Study characteristics, including study quality were extracted and entered into a pre-pilot data collection sheet. Descriptive statistics were calculated. On an exploratory basis, random forest and gradient boosting machine learning algorithms were used to examine the influence of article characteristics on AAS. Results: In total, 586 studies with an AAS were analyzed. Overall, the mean AAS of the samples was 5. Twitter was the most popular social media platform for publicizing studies, accounting for 53.7%. In terms of study quality, only 19.1% of the studies were rated as having a high level of quality, with 41.8% of the studies deemed moderate quality. The type of social media platform, number of citations, impact factor, and study type were among the most influential characteristics of AAS in both models. In contrast, study quality was one of the least influential characteristics on the AAS. Conclusions: Social media platforms contributed the most to the AAS for orthodontic studies, whereas study quality had little impact on the AAS.

• 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.

• Asia Marketing Journal
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• v.22 no.3
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• pp.71-85
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• 2020

Social media has emerged as a major hub of engagement between brands and consumers in recent years, and allows user-generated content to serve as a powerful means of encouraging communication between the sides. However, it is challenging to negotiate user-generated content owing to its lack of structure and the enormous amount generated. This study focuses on the hashtag, a metadata tag that reflects customers' brand perception through social media platforms. Online users share their knowledge and impressions using a wide variety of hashtags. We examine hashtags that co-occur with particular branded hashtags on the social media platform, Instagram, to derive insights about brand perception. We apply text mining technology and network analysis to identify the perceptions of brand images among consumers on the site, where this helps distinguish among the diverse personalities of the brands. This study contributes to highlighting the value of hashtags in constructing brand personality in the context of online marketing.

• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.2026-2033
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• 2023

Due to Thailand's nuclear energy public acceptance problem, the understanding of nuclear energy public perception was the key factor affecting to re-consideration of the nuclear energy program. Thailand Institute of Nuclear Technology and its alliances together developed the classification model for the nuclear energy public perception from the big data comments on social media using Facebook using deep transfer learning. The objective was to insight into the Thailand nuclear energy public perception on Facebook social media platform using sentiment analysis. The supervised learning was used to generate up-to-date classification model with more than 80% accuracy to classify the public perception on nuclear power plant news on Facebook from 2009 to 2022. The majority of neutral sentiments (80%) represented the opportunity for Thailand to convince people to receive a better nuclear perception. Negative sentiments (14%) showed support for other alternative energies due to nuclear accident concerns while positive sentiments (6%) expressed support for innovative nuclear technologies.

• Journal of Technology Innovation
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• v.29 no.4
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• pp.125-160
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• 2021

Unlike existing social platforms that seek openness, an audio-based social platform is characterized by its limitations. This study uses the Value-Based Acceptance Model(VAM) to analyze the role that such limitations play in the user's acceptance of audio-based social media. In this study, restrictive properties are defined as access-limitation, communication-limitation, and content-limitation. This study aims to analyze the effect of each variable on the perceived value and usage of audio-based social media. The hypothesis test was conducted based on the survey responses total of 207 users and potential users. The results was analyzed that three limiting variables affect perceived benefit factors, usefulness and playfulness, and the user's acceptance intention. This study is significant in that it presents a model based on the VAM and provides guidance for new forms of social media growth.

• Journal of the Korea Convergence Society
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• v.12 no.12
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• pp.245-255
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• 2021

This study is an empirical study on how factors such as social factor, entertainment factor on the Wechat social media platform affect users' flow and addiction to use. Researchers thought that despite the increasing addiction of social media Wechat users, existing social media research is limited to service quality and satisfaction, so research on user flow and addiction is necessary. Therefore, the researchers try to through empirical analysis, the WeChat use to addiction path to social factor (social interactivity, payable) and entertainment factor (entertainment, life relevance), examine how WeChat user experience affects the use intention and satisfaction, and determine its role in the user's WeChat addiction and flow, and tested. The results of this study are expected to provide a new theoretical basis for future research on addiction use of social media.

• The Journal of Information Systems
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• v.32 no.1
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• pp.23-51
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• 2023

Purpose: Live commerce is a new type of electronic commerce in combination with live streaming services. It is expected to increase virtual presence in the context of online shopping by overcoming a lack of social interactions between sellers and buyers which have been raised as a limitation in electronic commerce. Drawing on the studies of communication media, this study examines how live commerce contributes to the increase of virtual presence which consists of telepresence and social presence. Telepresence refers to a buyer's perception that he or she is present at the physical shopping mall during live shopping streaming whereas social presence refers to a buyer's perception of social interaction with a seller which is human warm, social, sensitive, and personal. In this study, we verify key determinants of virtual presence and its consequences. More specifically, this study proposes virtual presence contributes to the increase of buyers' trust in products and further purchase intentions. Furthermore, we verify influential factors of virtual presence from the technical and influencer perspectives of live commerce. Design/methodology/approach: To test the proposed hypotheses, the partial least squares (PLS) analysis is conducted with a total of 250 data collected on users with experience in the TaoBao live streaming shopping platform. Findings: The results show that first, telepresence and social presence are increased by visibility, media richness and attractiveness in the context of live shopping streaming. Second, buyers' trust in product trust and purchase intentions are positively influenced by telepresence and social presence. Finally, buyers' trust in product has a direct, positve effect on their purchase intentions. Overall, the findings offer new insights into the studies of electronic commerce by introducting the concepts of virtual presence and media richness from the literature of communication media in the field of live commerce.

• Journal of Distribution Science
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• v.22 no.8
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• pp.109-124
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• 2024

Purpose: This study examines short-platform content that is becoming more popular on social media. This study investigates the relationship between short-form content experience, consumer participation behavior, and consideration set. Furthermore, the mediating effect on empathy factors was confirmed during consumers' experience with short-form content. Data and methodology: Prior studies were reviewed, and hypotheses were developed. Consumers who had watched and shared short-form content within the previous three months were targeted to achieve the study's goal. A structured questionnaire was used to conduct the survey. Results: First, users of short-platform content with practical, playful, and emotional value did not confirm a positive effect on consumer participation behavior. However,short-form content with social value positively impacted consumer participation behavior. Second, consumer participation in short-form content was confirmed to positively affect the consideration set. Third, in terms of the mediating effect of empathy factors, short-platform content with practical, social, and emotional values partially mediates consumer participation behavior, whereas short-platform content with playfulness value completely mediates consumer participation behavior. Conclusions: The results of this study have academic and practical implications for the recent marketing field. In particular, research has been conducted in the field of digital marketing, which has recently changed rapidly.

• Asia-Pacific Journal of Business
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• v.15 no.2
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• pp.1-22
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• 2024

Purpose - The Chinese fan community includes a significant number of young and middle-aged individuals, playing a crucial role in emotional mobilization and social engagement. In recent years, the impact of Celebrity Pairing or Character Pairing (CP) on Weibo has grown notably, partly due to features like Super Topics and Hot Searches. This phenomenon has enhanced fan engagement, resulting in heightened participation in discussions and interactions on the platform. Our study targets CP fans of movies and television dramas on Weibo and aims to identify the factors that drive their emotional sharing. Design/methodology/approach - The research methodology integrates Self-Determination Theory and Social Sharing of Emotion Theory within the EASI (Emotion, Attachment, and Social Integration) model. This approach aims to uncover how CP fans meet their emotional needs via social media and determine the factors influencing their sharing intentions and behaviours. Data were collected through online surveys, yielding 504 valid responses Findings - The analysis, performed with SPSS and Smart PLS software, reveals that self-determination, interpersonal relationships, and social media tolerance significantly affect fans' intentions to share content. Specifically, intrinsic motivation, driven by self-determination, is a critical factor in CP fans' propensity to share content, highlighting the importance of 'inward socialization.' Additionally, the study finds that external factors, like the social media environment, play a more minor role than internal motivators. Research implications or Originality - This research enhances quantitative research methodologies by identifying intrinsic and extrinsic motivations that satisfy the emotional needs of CP fans. It distinguishes between individual, interpersonal, and collective/social factors as motivational elements, providing insights into the emotional and psychological needs of the Chinese movie and TV drama fan community.

• Journal of KIISE
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• v.43 no.1
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• pp.96-105
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• 2016

Recently, social network services have changed by moving towards an open platform where, as well as simply allowing the building of relationships among users, various types of information can be generated and shared. Since existing user reputation management methods evaluate user reliability based on user profiles, explicit relations, and evaluation, they are not suitable for determining user reliability on social media due to few explicit evaluation. In this paper, we analyze social activities on social media and propose a new user reputation management method that considers implicit evaluation as well as explicit evaluation. The proposed method derives positive and negative implicit evaluation from social activities, and generates user reputation information by field in order to consider user expertise. It also considers the number of users that participate in evaluation in order to measure user influence. As a result, it generates the reputation information of users who have no explicit evaluation and creates user reputation information that is more suitable for social media.