• Title/Summary/Keyword: social media network

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A research for Social Learning method of using Social Media (소셜 미디어를 활용한 소셜 러닝 체제 연구)

  • Chang, Il-Su;Hong, Myung-Hui
    • 한국정보교육학회:학술대회논문집
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    • 2011.01a
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    • pp.233-240
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    • 2011
  • Social Media is the open online tool and media platform for sharing and participation of users opinion, experience, viewpoiont, so general situation that is one-side flowing from production to consume doesn't act, and while use of two-way, user create contents use of sharing and participation. This social media include Blog, Social Network Service(SNS), Wiki, User Create Contents(UCC), Micro Blog, 5 types. In broad terms, Social Learning is self-learning that user sharing with coperation and collective intelligence through Social Media, and in few wards Social Learning is learning for Social Media. In this research, we define Social Media and Social Learning, and research of method of use of Elementary Education.

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Evaluating the Characteristics of Subversive Basic Fashion Utilizing Text Mining Techniques (텍스트 마이닝(text mining) 기법을 활용한 서브버시브 베이식(subversive basics) 패션의 특성)

  • Minjung Im
    • Journal of Fashion Business
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    • v.27 no.5
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    • pp.78-92
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    • 2023
  • Fashion trends are actively disseminated through social media, which influences both their propagation and consumption. This study explored how users perceive subversive basic fashion in social media videos, by examining the associated concepts and characteristics. In addition, the factors contributing to the style's social media dissemination were identified and its distinctive features were analyzed. Through text mining analysis, 80 keywords were selected for semantic network and CONCOR analysis. TF-IDF and N-gram results indicate that subversive basic fashion involves transformative design techniques such as cutting or layering garments, emphasizing the body with thin fabrics, and creating bold visual effects. Topic modeling suggests that this fashion forms a subculture that resists mainstream norms, seeking individuality by creatively transforming the existing garments. CONCOR analysis categorized the style into six groups: forward-thinking unconventional fashion, bold and unique style, creative reworking, item utilization and combination, pursuit of easy and convenient fashion, and contemporary sensibility. Consumer actions, linked to social media, were shown to involve easily transforming and pursuing personalized styles. Furthermore, creating new styles through the existing clothing is seen as an economic and creative activity that fosters network formation and interaction. This study is significant as it addresses language expression limitations and subjectivity issues in fashion image analysis, revealing factors contributing to content reproduction through user-perceived design concepts and social media-conveyed fashion characteristics.

The Social Media Factor: How Platforms Impact Usability of Blackboard at Umm Al Qura University

  • Ahmed R Albashiri
    • 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.

A Study on the receptivity to Social Computing in International Trade (국제무역의 소셜 컴퓨팅 수용 가능성에 관한 연구)

  • Lim, Jae-Wook
    • International Commerce and Information Review
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    • v.13 no.3
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    • pp.55-74
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    • 2011
  • Web Service applications based on the social relation such as Social Network Service(SNS), Social Medias are making strong blast. Social Computing which is widely spreading to worldwide is affecting to our life including policies, economies, societies and culture. Based on Web 2.0, various services like as Social Collaboration, Social Publishing, Social Feedback are supplied, more evolved social computing services, Social Connection, Augmented Reality, will be served for the next days from now. These network based services, Social Network Service or Social Media frequently used terms, are not defined exactly and their characteristics are not gotten to the bottom yet. Theoretical and systematic studies on these themes are not made also. Applications to business area, especially the receptivity to social computing in international trade is barely made to these days. This study focuses on the concepts, characteristics and sorts of social computing and purposes to consider its possibilities of application of social computing to international trade. Considering the advantage of Social network service, it can be used in international trade, a kind of B2B transaction, while existing social network is mainly applied to B2e transaction.

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Research on the Discourse of Libraries During COVID-19 in YouTube Videos Using Topic Modeling and Social Network Analysis

  • Euikyung Oh;Ok Nam Park
    • Journal of Information Science Theory and Practice
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    • v.11 no.3
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    • pp.29-42
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    • 2023
  • This study explored issues related to the library in the COVID-19 era in YouTube videos in Korea. This study performed social network analysis and topic modeling analysis by collecting 479 YouTube videos, 20,545 words, and 8,379 channels related to COVID-19 and the library from 2019 to 2020. The study results confirmed that YouTube, a social media platform, was used as an important medium to connect users and physical libraries and provide/promote online library services. In the study, major topics and keywords such as quarantine, vlog, and library identity during the COVID-19 pandemic, library services and functions, and introductions and user guides of libraries were derived. Additionally, it was identified that videos about COVID-19 and the library are being produced by various actors (news and media channels, libraries, government agencies, librarians, and individual users). However, the study also identified that the actor network is fragmented through the channel network, showing a low density or weak linkage, and that the centrality of the library in the actor network is weak.

Exploring Twitter Follower-Networks of Startup Companies Employing Social Network Analysis and Cluster Analysis (소셜네트워크 분석과 클러스터 분석 방법을 활용한 스타트업 회사의 트위터 팔로워 네트워크에 대한 탐색적 연구)

  • Yu, Seunghee
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.14 no.4
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    • pp.199-209
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    • 2019
  • The importance of business strategy for successful social media engagement has quickly increased as more businesses engage in social media. The importance is even greater for startup companies because startup companies are genuinely new to business, and they need to increase their presence in the market, and quickly access future customers. The objective of this paper lies in exploring key indicators of social media engagements by selected startup companies. The key indicators include two aspects of social media usages by the companies: i) overall social media activities, and ii) properties of network structure of the information flow platform provided by social media service. To better assess and evaluate the key indicators of social media usages by startup companies, the indicators will be compared with those of selected large established companies. Twitter is selected as a social media service for the analysis of this paper, and using Twitter REST API, data regarding the key indicators of overall Twitter activities and the Twitter follower-network of each company in the sample are collected. Then, the data are analyzed using social network analysis and hierarchical clustering analysis to examine the characteristics of the follower-network structures and to compare the characteristics between startup companies and established companies. The results show that most indicators are significantly different across startup companies and established companies. One key interesting finding is that the startup companies have proportionally more influencers in their follower-networks than the established companies have. Another interesting finding is that the follower-networks of startup companies in the sample have higher modularity and higher transitivity, suggesting that the startup companies tend to have a proportionally larger number of communities of users in their follower-networks, and the users in the networks are more tightly connected and cohesive internally. The key business implication for the future social media engagement efforts by startup companies in general is that startup companies may need to focus on getting more attention from influencers and promoting more cohesive communities in their follower-networks to appreciate the potential benefits of social media in the early stage of business of startup companies.

Improved Decision Tree Classification (IDT) Algorithm For Social Media Data

  • Anu Sharma;M.K Sharma;R.K Dwivedi
    • International Journal of Computer Science & Network Security
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    • v.24 no.6
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    • pp.83-88
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    • 2024
  • In this paper we used classification algorithms on social networking. We are proposing, a new classification algorithm called the improved Decision Tree (IDT). Our model provides better classification accuracy than the existing systems for classifying the social network data. Here we examined the performance of some familiar classification algorithms regarding their accuracy with our proposed algorithm. We used Support Vector Machines, Naïve Bayes, k-Nearest Neighbors, decision tree in our research and performed analyses on social media dataset. Matlab is used for performing experiments. The result shows that the proposed algorithm achieves the best results with an accuracy of 84.66%.

Quantifying Influence in Social Networks and News Media

  • Yun, Hong-Won
    • Journal of information and communication convergence engineering
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    • v.10 no.2
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    • pp.135-140
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    • 2012
  • Massive numbers of users of social networks share various types of information such as opinions, news, and ideas in real time. As a new form of social network, Twitter is a particularly useful information source. Studying influence can help us better understand the role of social networks. The popularity of social networks like Twitter is primarily measured by the number of followers. The number of followers in Twitter and the number of users exposed to news media are important factors in measuring influence. We chose Twitter and the New York Times as representative media to analyze the influence and present an empirical analysis of these datasets. When the correlation between the number of followers in Twitter and the number of users exposed to the New York Times is computed, the result is moderately high. The correlation between the number of users exposed to the New York Times and the number of sections including the users on it, was found to be very high. We measure the normalized influence score using our proposed expression based on the two correlation coefficients.

Knowledge Management Research Based on Social Network Theories: A Review with Future Directions

  • Tae Hun Kim
    • Asia pacific journal of information systems
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    • v.32 no.1
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    • pp.168-190
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    • 2022
  • This review aims to synthesize social network theories by drawing on the importance of social network perspectives in understanding knowledge management with technology in organizations. I provide an overview of prior social network research with the following core ideas: the primacy of relations between organizational actors, the utility of actors' embeddedness in social fields, the social utility of network connections, and the structural patterning of social life. On top of that, I summarize critical social perspectives (the social capital theory, the structural hole theory, the embeddedness perspective, the social exchange theory, the organizational learning theory, and the innovation diffusion theory) to suggest potential research questions for future studies in social network research in the knowledge management discipline.

On the Scale in the Kingdom of Saudi Arabia: Facebook vs. Snapchat

  • Alghamdi, Deena
    • International Journal of Computer Science & Network Security
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    • v.21 no.12
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    • pp.131-136
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    • 2021
  • This research aims to analyse the practices adopted by social media users in the Kingdom of Saudi Arabia (KSA), specifically users of Facebook and Snapchat. To collect data from participants, a questionnaire was used, generating 915 responses. The analysis of the data shows a clear preference for Snapchat over Facebook in the KSA, where 89% of the participants have accounts on Snapchat compared to 66% of them with accounts on Facebook. Moreover, the preference for Snapchat over Facebook has been clearly shown in the daily usage of participants, where 83% of those with Snapchat accounts can be described as very active users. They have accessed their Snapchat accounts at least once a day compared to only 15% of Facebook users. Different reasons were provided by the participants explaining the practices they adopted. We believe that such research could help social media applications' designers and policy makers to understand the behaviour of users in the KSA when using social media applications and the rationale behind their behaviour and preferences. This understanding could help improve the performance of current applications and new ones.