Ana Paula Appel
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Statistical and Nonlinear Physics top 10%
- Information Systems top 10%
- Computer Networks and Communications
- Co-authors
- Jure LeskovecChristos FaloutsosCharalampos E. TsourakakisU KangM CohenZeev GroswasserCláudio PinhanezPaulo Cavalin
- Topics
- Complex Network Analysis Techniques (11 papers)Topic Modeling (5 papers)Opinion Dynamics and Social Influence (5 papers)
- Cited by
- Statistical and Nonlinear PhysicsComputer Vision and Pattern RecognitionArtificial Intelligence
- Partner nations
- BrazilUnited StatesIsrael
In The Last Decade
Ana Paula Appel
23 papers receiving 252 citations
Peers
Comparison fields: 5 of 66
- Artificial Intelligence 109
- Computer Vision and Pattern Recognition 94
- Statistical and Nonlinear Physics 71
- Information Systems 59
- Computer Networks and Communications 48
Countries citing papers authored by Ana Paula Appel
This map shows the geographic impact of Ana Paula Appel'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 Ana Paula Appel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ana Paula Appel more than expected).
Fields of papers citing papers by Ana Paula Appel
This network shows the impact of papers produced by Ana Paula Appel. 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 Ana Paula Appel. The network helps show where Ana Paula Appel may publish in the future.
Co-authorship network of co-authors of Ana Paula Appel
This figure shows the co-authorship network connecting the top 25 collaborators of Ana Paula Appel. A scholar is included among the top collaborators of Ana Paula Appel 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 Ana Paula Appel. Ana Paula Appel 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 | 7 | |
| 3 | 15 | |
| 4 | 1 | |
| 5 | 6 | |
| 6 | 1 | |
| 7 | 5 | |
| 8 | 2 | |
| 9 | 2 | |
| 10 | 0 | |
| 11 | 13 | |
| 12 | 8 | |
| 13 | 6 | |
| 14 | 2 | |
| 15 | 6 | |
| 16 | 0 | |
| 17 | 2 | |
| 18 | 9 | |
| 19 | 35 | |
| 20 | 57 |
About Ana Paula Appel
Ana Paula Appel is a scholar working on Statistical and Nonlinear Physics, Family Practice and Management Science and Operations Research, having authored 26 papers that have together received 274 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (11 papers), Topic Modeling (5 papers) and Opinion Dynamics and Social Influence (5 papers). The work is most often cited by research in Statistical and Nonlinear Physics (71 citations), Computer Vision and Pattern Recognition (94 citations) and Artificial Intelligence (109 citations). Ana Paula Appel has collaborated with scholars based in Brazil, United States and Israel. Frequent co-authors include Jure Leskovec, Christos Faloutsos, Charalampos E. Tsourakakis, U Kang, M Cohen, Zeev Groswasser, Cláudio Pinhanez, Paulo Cavalin, Estevam Hruschka and Víctor Henrique Alves Ribeiro. Their work appears in journals such as Journal of Service Research, Lecture notes in computer science and Brain Injury.
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.