Ling Feng
- Statistical and Nonlinear Physics top 2%
- Economics and Econometrics top 5%
- Finance top 5%
- Information Systems top 5%
- Sociology and Political Science
- Co-authors
- H. Eugene StanleyBaowen LiYanqing HuBoris PodobnikShlomo HavlinZeyu ZhengTobias PreisChristopher Monterola
- Topics
- Complex Network Analysis Techniques (17 papers)Opinion Dynamics and Social Influence (12 papers)Complex Systems and Time Series Analysis (9 papers)
- Partner nations
- SingaporeChinaUnited States
In The Last Decade
Ling Feng
40 papers receiving 772 citations
Peers
Comparison fields: 5 of 128
- Statistical and Nonlinear Physics 322
- Economics and Econometrics 277
- Finance 135
- Information Systems 123
- Sociology and Political Science 94
Countries citing papers authored by Ling Feng
This map shows the geographic impact of Ling Feng'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 Ling Feng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ling Feng more than expected).
Fields of papers citing papers by Ling Feng
This network shows the impact of papers produced by Ling Feng. 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 Ling Feng. The network helps show where Ling Feng may publish in the future.
Co-authorship network of co-authors of Ling Feng
This figure shows the co-authorship network connecting the top 25 collaborators of Ling Feng. A scholar is included among the top collaborators of Ling Feng 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 Ling Feng. Ling Feng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 9 | |
| 5 | 3 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 20 | |
| 9 | 29 | |
| 10 | 17 | |
| 11 | 8 | |
| 12 | 1 | |
| 13 | 4 | |
| 14 | 2 | |
| 15 | 79 | |
| 16 | 71 | |
| 17 | Tree model guided candidate generation for mining frequent subtrees from XML | 21 |
| 18 | Multimedia Retrieval (Data-Centric Systems and Applications) | 11 |
| 19 | Stock movement prediction and N-dimensional inter-transaction association rules | 60 |
| 20 | AN APPROXIMATION METHOD FOR THE BOX-COUNTING DIMENSION OF FRACTAL CURVE | 1 |
About Ling Feng
Ling Feng is a scholar working on Statistical and Nonlinear Physics, Finance and Economics and Econometrics, having authored 44 papers that have together received 806 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (17 papers), Opinion Dynamics and Social Influence (12 papers) and Complex Systems and Time Series Analysis (9 papers). The work is most often cited by research in Statistical and Nonlinear Physics (322 citations), Finance (135 citations) and Economics and Econometrics (277 citations). Ling Feng has collaborated with scholars based in Singapore, China and United States. Frequent co-authors include H. Eugene Stanley, Baowen Li, Yanqing Hu, Boris Podobnik, Shlomo Havlin, Zeyu Zheng, Tobias Preis, Christopher Monterola, Jiawei Han and Hongjun Lü. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications and PLoS ONE.
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.