Michael Brautbar
Impact in
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- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
- Transportation top 10%
- Human Mobility and Location-Based Analysis
Papers in
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- Complex Network Analysis Techniques 7
- Opinion Dynamics and Social Influence 3
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- Complexity and Algorithms in Graphs 3
- Co-authors
- Jennifer Chayes (5 shared papers)Christian Borgs (5 shared papers)Brendan Lucier (2 shared papers)Michael J. Kearns (2 shared papers)Shang‐Hua Teng (3 shared papers)Sanjeev Khanna (2 shared papers)Moez Draief (1 shared paper)
- Journals
- Internet Mathematics (1 paper)Lecture notes in computer science (4 papers)ScholarlyCommons (University of Pennsylvania) (1 paper)
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
Michael Brautbar
7 papers receiving 605 citations
Michael Brautbar's Hit Papers
Peers
Comparison fields: 5 of 49
- Statistical and Nonlinear Physics 493
- Transportation 43
- Computer Networks and Communications 154
- Computer Science Applications 36
- Management Science and Operations Research 72
Countries citing papers authored by Michael Brautbar
This map shows the geographic impact of Michael Brautbar'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 Michael Brautbar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Brautbar more than expected).
Fields of papers citing papers by Michael Brautbar
This network shows the impact of papers produced by Michael Brautbar. 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 Michael Brautbar. The network helps show where Michael Brautbar may publish in the future.
Co-authors
The 7 scholars most cited alongside Michael Brautbar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Maximizing Social Influence in Nearly Optimal Time Hit paper breakdown → | 2013 | 497 |
| 2 | 2012 | 34 | |
| 3 | 2013 | 24 | |
| 4 | 2012 | 22 | |
| 5 | Local Algorithms for Finding Interesting Individuals in Large Networks | 2010 | 22 |
| 6 | 2011 | 16 | |
| 7 | Sublinear Time Algorithm for PageRank Computations and Related Applications | 2012 | 1 |
| 8 | 2013 | 1 |
About Michael Brautbar
Michael Brautbar is a scholar working on Statistical and Nonlinear Physics, Computational Theory and Mathematics, Computer Networks and Communications, Artificial Intelligence and Management Science and Operations Research, having authored 8 papers that have together received 617 indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (7 papers), Opinion Dynamics and Social Influence (3 papers), Complexity and Algorithms in Graphs (3 papers), Peer-to-Peer Network Technologies (2 papers), Advanced Graph Neural Networks (2 papers), Optimization and Search Problems (1 paper), Network Security and Intrusion Detection (1 paper) and Game Theory and Applications (1 paper). The work is most often cited by research in Statistical and Nonlinear Physics (493 citations), Transportation (43 citations), Computer Networks and Communications (154 citations), Computer Science Applications (36 citations) and Management Science and Operations Research (72 citations). Michael Brautbar has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Jennifer Chayes, Christian Borgs, Brendan Lucier, Michael J. Kearns, Shang‐Hua Teng, Sanjeev Khanna and Moez Draief. Their work appears in journals such as Internet Mathematics, Lecture notes in computer science and ScholarlyCommons (University of Pennsylvania).
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.