Jon Kleinberg
Impact in
- Statistical and Nonlinear Physics top 0.01%
- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
- Information Systems top 0.01%
- Web Data Mining and Analysis
- Spam and Phishing Detection
Papers in
-
- Complex Network Analysis Techniques 115
- Opinion Dynamics and Social Influence 87
-
- Game Theory and Applications 45
- Auction Theory and Applications 20
- Co-authors
- Éva Tardos (27 shared papers)Jure Leskovec (20 shared papers)David Kempe (18 shared papers)David Liben‐Nowell (8 shared papers)Lars Bäckström (13 shared papers)David A. Easley (26 shared papers)Daniel P. Huttenlocher (17 shared papers)Christos Faloutsos (3 shared papers)
- Journals
- SIAM Journal on Computing (9 papers)Proceedings of the National Academy of Sciences (8 papers)Journal of the ACM (8 papers)Journal of Computer and System Sciences (7 papers)Lecture notes in computer science (50 papers)
- Partner nations
- United StatesIsraelUnited Kingdom
In The Last Decade
Jon Kleinberg
370 papers receiving 57.0k citations
Jon Kleinberg's Hit Papers
Peers
Comparison fields: 5 of 224
- Statistical and Nonlinear Physics 27.5k
- Information Systems 13.3k
- Artificial Intelligence 18.6k
- Computer Networks and Communications 12.9k
- Communication 3.4k
Countries citing papers authored by Jon Kleinberg
This map shows the geographic impact of Jon Kleinberg'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 Jon Kleinberg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jon Kleinberg more than expected).
Fields of papers citing papers by Jon Kleinberg
This network shows the impact of papers produced by Jon Kleinberg. 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 Jon Kleinberg. The network helps show where Jon Kleinberg may publish in the future.
Co-authors
The 25 scholars most cited alongside Jon Kleinberg, 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 382 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Authoritative sources in a hyperlinked environment Hit paper breakdown → | 1999 | 6584 |
| 2 | Maximizing the spread of influence through a social network Hit paper breakdown → | 2003 | 5593 |
| 3 | The link‐prediction problem for social networks Hit paper breakdown → | 2007 | 2426 |
| 4 | Graph evolution Hit paper breakdown → | 2007 | 1869 |
| 5 | Graphs over time Hit paper breakdown → | 2005 | 1684 |
| 6 | The small-world phenomenon Hit paper breakdown → | 2000 | 1335 |
| 7 | Group formation in large social networks Hit paper breakdown → | 2006 | 1334 |
| 8 | Authoritative sources in a hyperlinked environment Hit paper breakdown → | 1998 | 1310 |
| 9 | The link prediction problem for social networks Hit paper breakdown → | 2003 | 1229 |
| 10 | Navigation in a small world Hit paper breakdown → | 2000 | 1220 |
| 11 | Networks, Crowds, and Markets: Network Dynamics: Structural Models Hit paper breakdown → | 2010 | 1193 |
| 12 | Networks, Crowds, and Markets: Network Dynamics: Population Models Hit paper breakdown → | 2010 | 1193 |
| 13 | Meme-tracking and the dynamics of the news cycle Hit paper breakdown → | 2009 | 1103 |
| 14 | Predicting positive and negative links in online social networks Hit paper breakdown → | 2010 | 1090 |
| 15 | Signed networks in social media Hit paper breakdown → | 2010 | 940 |
| 16 | Bursty and Hierarchical Structure in Streams Hit paper breakdown → | 2003 | 930 |
| 17 | Bursty and hierarchical structure in streams Hit paper breakdown → | 2002 | 857 |
| 18 | Differences in the mechanics of information diffusion across topics Hit paper breakdown → | 2011 | 814 |
| 19 | Influential Nodes in a Diffusion Model for Social Networks Hit paper breakdown → | 2005 | 737 |
| 20 | Maximizing the spread of influence through a social network Hit paper breakdown → | 2003 | 730 |
About Jon Kleinberg
Jon Kleinberg is a scholar working on Statistical and Nonlinear Physics, Management Science and Operations Research, Computer Networks and Communications, Computational Theory and Mathematics and Artificial Intelligence, having authored 382 papers that have together received 60.4k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (115 papers), Opinion Dynamics and Social Influence (87 papers), Game Theory and Applications (45 papers), Optimization and Search Problems (39 papers), Complexity and Algorithms in Graphs (30 papers), Auction Theory and Applications (20 papers), Peer-to-Peer Network Technologies (20 papers) and Advanced Graph Theory Research (19 papers). The work is most often cited by research in Statistical and Nonlinear Physics (27.5k citations), Information Systems (13.3k citations), Artificial Intelligence (18.6k citations), Computer Networks and Communications (12.9k citations) and Communication (3.4k citations). Jon Kleinberg has collaborated with scholars based in United States, Israel and United Kingdom. Frequent co-authors include Éva Tardos, Jure Leskovec, David Kempe, David Liben‐Nowell, Lars Bäckström, David A. Easley, Daniel P. Huttenlocher, Christos Faloutsos, Prabhakar Raghavan and Sendhil Mullainathan. Their work appears in journals such as SIAM Journal on Computing, Proceedings of the National Academy of Sciences, Journal of the ACM, Journal of Computer and System Sciences and Lecture notes in computer science.
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.