Wingyan Chung
Professor, Kneedler Distinguished Professor of CIS | Western Carolina University
Cullowhee, NC, UNITED STATES
Wingyan Chung is an information systems scholar with expertise in business analytics, information systems and human-computer interaction.
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Biography
Wingyan Chung is an information systems scholar and educator with expertise in business analytics, information systems, social media analytics, business intelligence, cybersecurity, data and text mining, Web analytics, knowledge management and human-computer interaction. Chung received his doctorate in Management Information Systems from the University of Arizona. He has more than 100 refereed publications in Journal of Management Information Systems, Information & Management, Decision Support Systems, Communications of the ACM, IEEE Computer, Scientific Reports, IJHCS, Journal of the Association for Information Science and Technology, and ICIS, among others. Recognitions include top ranking in BI and analytics, press coverage in ForwardFlorida and in SIGCSE and Senior Member awards from AAAI, ACM and IEEE.
Industry Expertise (2)
Business Services
Education/Learning
Areas of Expertise (5)
Machine Learning
Social Media Analytics
Business Analytics
Information Systems
Business Intelligence
Accomplishments (3)
Excellence in Research Award (professional)
College of Business
Hunter Scholar Award (professional)
Western Carolina University
Excellence in Research Award (professional)
University of Central Florida
Education (3)
University of Arizona: Ph.D., Management Information Systems
The Chinese University of Hong Kong: B.B.A., Business Administration
he Chinese University of Hong Kong: M.S., Information & Technology Management
Affiliations (3)
- International Journal of Engineering Business Management : Associate Editor
- Informatics : Editorial Board Member
- Computer Information Systems at WCU : Academic Advisor
Links (5)
Languages (1)
- English
Articles (5)
A Low-Cost Multi-Failure Resilient Replication Scheme for High-Data Availability in Cloud Storage
IEEE2020 Data availability is one of the most important performance factors in cloud storage systems. To enhance data availability, replication is a common approach to handle the machine failures. However, previously proposed replication schemes cannot effectively handle both correlated and non-correlated machine failures, especially while increasing the data availability with limited resources.
A computational framework for social-media-based business analytics and knowledge creation: empirical studies of CyTraSS
Enterprise Information Systems2020 Social media (SM) platforms greatly facilitate business information sharing, customer relationship building, and client emotion expression. However, managing knowledge acquired from SM messages is challenged by limited human cognitive capability.
Rockstar Effect in Distributed Project Management on GitHub Social Networks
Proceedings of the 2019 Pre-Icis Sigdsa Symposium2020 The internet has become increasingly social, opening up new space for online collaboration and distributed project management. Decentralized management techniques such as open-source software, distributed development, and software-as-a-service allow software developers to easily connect online and to solve complex problems collaboratively.
Efficient parameter selection for support vector machines
Enterprise Information Systems2019 The support vector machines (SVM) is a popular classification method. Many users may not well tune hyperparameters because this step is time-consuming. However, the performance of SVM relies on the values of hyperparameters.
CrossSimON: A Novel Probabilistic Approach to Cross-Platform Online Social Network Simulation
IEEE2019 The increasing popularity and diversity of online social networks (OSNs) have attracted more and more people to participate in multiple OSNs. Learning users' behavior and information diffusion across platforms is critical for cyber threat detection, but it is still a challenge due to the surge of users participating in multiple social platforms.
