Yue Jin
- Economics and Econometrics top 10%
- Marketing top 10%
- Sociology and Political Science
- Artificial Intelligence
- Information Systems and Management top 10%
- Co-authors
- Dongyang ZhangJinghua HuangAmy K. FerketichJian YuanMajed AbbasYuk Ming TangEric E. SeiberShuangqing Wei
- Topics
- Reinforcement Learning in Robotics (8 papers)Distributed Control Multi-Agent Systems (4 papers)Digital Marketing and Social Media (4 papers)
- Journals
- Journal of Environmental ManagementInternational Journal of Environmental Research and Public HealthPreventive Medicine
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Yue Jin
23 papers receiving 387 citations
Peers
Comparison fields: 5 of 77
- Economics and Econometrics 124
- Marketing 88
- Sociology and Political Science 87
- Artificial Intelligence 53
- Information Systems and Management 51
Countries citing papers authored by Yue Jin
This map shows the geographic impact of Yue Jin'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 Yue Jin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yue Jin more than expected).
Fields of papers citing papers by Yue Jin
This network shows the impact of papers produced by Yue Jin. 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 Yue Jin. The network helps show where Yue Jin may publish in the future.
Co-authorship network of co-authors of Yue Jin
This figure shows the co-authorship network connecting the top 25 collaborators of Yue Jin. A scholar is included among the top collaborators of Yue Jin 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 Yue Jin. Yue Jin 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 | 17 | |
| 4 | 1 | |
| 5 | 19 | |
| 6 | 45 | |
| 7 | 31 | |
| 8 | 3 | |
| 9 | 9 | |
| 10 | 1 | |
| 11 | 3 | |
| 12 | 2 | |
| 13 | 14 | |
| 14 | 65 | |
| 15 | What Influences Content Popularity? An Empirical Investigation of Voting in Social Q&A Communities. | 10 |
| 16 | 18 | |
| 17 | 10 | |
| 18 | 11 | |
| 19 | 18 | |
| 20 | 31 |
About Yue Jin
Yue Jin is a scholar working on Marketing, Information Systems and Management and Artificial Intelligence, having authored 24 papers that have together received 396 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (8 papers), Distributed Control Multi-Agent Systems (4 papers) and Digital Marketing and Social Media (4 papers). The work is most often cited by research in Marketing (88 citations), Information Systems and Management (51 citations) and Economics and Econometrics (124 citations). Yue Jin has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Dongyang Zhang, Jinghua Huang, Amy K. Ferketich, Jian Yuan, Majed Abbas, Yuk Ming Tang, Eric E. Seiber, Shuangqing Wei, Pengcheng Wang and Xudong Zhang. Their work appears in journals such as Journal of Environmental Management, International Journal of Environmental Research and Public Health and Preventive Medicine.
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.