Kai‐Yu Tang
- Sociology and Political Science top 2%
- Information Systems and Management top 0.5%
- Computer Science Applications top 1%
- Marketing top 5%
- Education top 5%
- Co-authors
- Chun‐Hua HsiaoJung‐Jung ChangGwo‐Jen HwangChing‐Yi ChangChin‐Chung TsaiYun‐Fang TuTzu‐Chiang LinRaghu Raman
- Topics
- Technology Adoption and User Behaviour (17 papers)Digital Marketing and Social Media (16 papers)Online Learning and Analytics (7 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEIEEE Access
In The Last Decade
Kai‐Yu Tang
52 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 140
- Sociology and Political Science 606
- Information Systems and Management 603
- Computer Science Applications 256
- Marketing 238
- Education 222
Countries citing papers authored by Kai‐Yu Tang
This map shows the geographic impact of Kai‐Yu Tang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Kai‐Yu Tang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kai‐Yu Tang more than expected).
Fields of papers citing papers by Kai‐Yu Tang
This network shows the impact of papers produced by Kai‐Yu Tang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Kai‐Yu Tang. The network helps show where Kai‐Yu Tang may publish in the future.
Co-authorship network of co-authors of Kai‐Yu Tang
This figure shows the co-authorship network connecting the top 25 collaborators of Kai‐Yu Tang. A scholar is included among the top collaborators of Kai‐Yu Tang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kai‐Yu Tang. Kai‐Yu Tang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 3 | |
| 4 | 1 | |
| 5 | 13 | |
| 6 | 1 | |
| 7 | 42 | |
| 8 | 6 | |
| 9 | 19 | |
| 10 | 8 | |
| 11 | Trends in artificial intelligence-supported e-learning: a systematic review and co-citation network analysis (1998–2019)breakdown → | 199 |
| 12 | 26 | |
| 13 | 19 | |
| 14 | 29 | |
| 15 | How Has E-Book Research Evolved? A Bibliometric Comparison of International Journal Publications (2000-2019) | 3 |
| 16 | 37 | |
| 17 | 69 | |
| 18 | 7 | |
| 19 | A co-citation network of young children's learning with technology | 5 |
| 20 | Investigating the Success Factors for the Acceptance of Mobile Healthcare Technology. | 7 |
About Kai‐Yu Tang
Kai‐Yu Tang is a scholar working on Information Systems and Management, Computer Science Applications and Developmental and Educational Psychology, having authored 54 papers that have together received 1.6k indexed citations. Recurring topics across this work include Technology Adoption and User Behaviour (17 papers), Digital Marketing and Social Media (16 papers) and Online Learning and Analytics (7 papers). The work is most often cited by research in Information Systems and Management (603 citations), Health Informatics (65 citations) and Computer Science Applications (256 citations). Kai‐Yu Tang has collaborated with scholars based in Taiwan, China and India. Frequent co-authors include Chun‐Hua Hsiao, Jung‐Jung Chang, Gwo‐Jen Hwang, Ching‐Yi Chang, Chin‐Chung Tsai, Yun‐Fang Tu, Tzu‐Chiang Lin, Raghu Raman, Prema Nedungadi and Yu-Sheng Su. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and IEEE Access.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.