Jure Leskovec
Impact in
- Statistical and Nonlinear Physics top 0.01%
- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
- Artificial Intelligence top 0.01%
- Advanced Graph Neural Networks
- Topic Modeling
Papers in
-
- Complex Network Analysis Techniques 102
- Opinion Dynamics and Social Influence 67
-
- Advanced Graph Neural Networks 45
- Topic Modeling 35
- Co-authors
- Aditya Grover (2 shared papers)Jon Kleinberg (20 shared papers)Christos Faloutsos (19 shared papers)Julian McAuley (13 shared papers)Jaewon Yang (6 shared papers)Seth A. Myers (5 shared papers)Daniel P. Huttenlocher (8 shared papers)Jaewon Yang (7 shared papers)
- Journals
- Nature (8 papers)ACM Transactions on Knowledge Discovery from Data (4 papers)Science (4 papers)Nature Communications (3 papers)Nature Methods (3 papers)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
Jure Leskovec
287 papers receiving 60.7k citations
Jure Leskovec's Hit Papers
Peers
Comparison fields: 5 of 232
- Statistical and Nonlinear Physics 26.6k
- Artificial Intelligence 25.9k
- Transportation 4.5k
- Health Informatics 721
- Information Systems 11.3k
Countries citing papers authored by Jure Leskovec
This map shows the geographic impact of Jure Leskovec'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 Jure Leskovec with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jure Leskovec more than expected).
Fields of papers citing papers by Jure Leskovec
This network shows the impact of papers produced by Jure Leskovec. 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 Jure Leskovec. The network helps show where Jure Leskovec may publish in the future.
Co-authors
The 25 scholars most cited alongside Jure Leskovec, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 298 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | node2vec Hit paper breakdown → | 2016 | 7572 |
| 2 | Friendship and mobility Hit paper breakdown → | 2011 | 2342 |
| 3 | Cost-effective outbreak detection in networks Hit paper breakdown → | 2007 | 1948 |
| 4 | Graph evolution Hit paper breakdown → | 2007 | 1869 |
| 5 | Graphs over time Hit paper breakdown → | 2005 | 1684 |
| 6 | The dynamics of viral marketing Hit paper breakdown → | 2007 | 1459 |
| 7 | Community Structure in Large Networks: Natural Cluster Sizes and the Absence of Large Well-Defined Clusters Hit paper breakdown → | 2009 | 1315 |
| 8 | Learning to Discover Social Circles in Ego Networks Hit paper breakdown → | 2012 | 1244 |
| 9 | Hidden factors and hidden topics Hit paper breakdown → | 2013 | 1208 |
| 10 | Meme-tracking and the dynamics of the news cycle Hit paper breakdown → | 2009 | 1103 |
| 11 | Predicting positive and negative links in online social networks Hit paper breakdown → | 2010 | 1090 |
| 12 | Scientific discovery in the age of artificial intelligence Hit paper breakdown → | 2023 | 1070 |
| 13 | Foundation models for generalist medical artificial intelligence Hit paper breakdown → | 2023 | 1062 |
| 14 | Mobility network models of COVID-19 explain inequities and inform reopening Hit paper breakdown → | 2020 | 1054 |
| 15 | Defining and evaluating network communities based on ground-truth Hit paper breakdown → | 2013 | 1050 |
| 16 | Signed networks in social media Hit paper breakdown → | 2010 | 940 |
| 17 | Modeling polypharmacy side effects with graph convolutional networks Hit paper breakdown → | 2018 | 922 |
| 18 | Higher-order organization of complex networks Hit paper breakdown → | 2016 | 883 |
| 19 | Sampling from large graphs Hit paper breakdown → | 2006 | 841 |
| 20 | Mining of Massive Datasets Hit paper breakdown → | 2014 | 808 |
About Jure Leskovec
Jure Leskovec is a scholar working on Statistical and Nonlinear Physics, Artificial Intelligence, Information Systems, Communication and Computer Vision and Pattern Recognition, having authored 298 papers that have together received 62.7k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (102 papers), Opinion Dynamics and Social Influence (67 papers), Advanced Graph Neural Networks (45 papers), Topic Modeling (35 papers), Data Visualization and Analytics (16 papers), Spam and Phishing Detection (16 papers), Social Media and Politics (15 papers) and Recommender Systems and Techniques (15 papers). The work is most often cited by research in Statistical and Nonlinear Physics (26.6k citations), Artificial Intelligence (25.9k citations), Transportation (4.5k citations), Health Informatics (721 citations) and Information Systems (11.3k citations). Jure Leskovec has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Aditya Grover, Jon Kleinberg, Christos Faloutsos, Julian McAuley, Jaewon Yang, Seth A. Myers, Daniel P. Huttenlocher, Jaewon Yang, Lars Bäckström and Marinka Žitnik. Their work appears in journals such as Nature, ACM Transactions on Knowledge Discovery from Data, Science, Nature Communications and Nature Methods.
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.