Ariel D. Procaccia

161 papers receiving 3.6k citations

Peers

Ariel D. Procaccia
Comparison fields: 5 of 113
  • Management Science and Operations Research 2.2k
  • Economics and Econometrics 2.3k
  • General Decision Sciences 93
  • Safety Research 410
  • Computational Theory and Mathematics 548
Replace Vincent Conitzer with:
Vincent Conitzer United States
Moshe Tennenholtz Israel
Jeffrey S. Rosenschein Israel
Dov Monderer Israel
Francesca Rossi Italy
Kate Larson Canada
Wiebe van der Hoek United Kingdom
Carles Sierra Spain
Michael A. Trick United States
Maytal Saar‐Tsechansky United States
Ariel D. Procaccia relative to Vincent Conitzer United States Vincent Conitzer's profile →
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Citations per year

Countries citing papers authored by Ariel D. Procaccia

Since Specialization
Citations

This map shows the geographic impact of Ariel D. Procaccia'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 Ariel D. Procaccia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ariel D. Procaccia more than expected).

Fields of papers citing papers by Ariel D. Procaccia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ariel D. Procaccia. 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 Ariel D. Procaccia. The network helps show where Ariel D. Procaccia may publish in the future.

Co-authors

The 25 scholars most cited alongside Ariel D. Procaccia, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ariel D. Procaccia Line = papers co-authored together Ariel D. Procaccia links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 167 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016155
2 2009147
3 2019127
4 2007104
5 2019102
6 2012102
7 2010101
8 201290
9 200785
10 201882
11 201379
12 200976
13 201375
14 201474
15 201570
16
Complexity of unweighted coalitional manipulation under some common voting rules
200969
17 201469
18 201063
19 200863
20 201560

About Ariel D. Procaccia

Ariel D. Procaccia is a scholar working on Management Science and Operations Research, Economics and Econometrics, Artificial Intelligence, Computational Theory and Mathematics and Safety Research, having authored 167 papers that have together received 3.7k indexed citations. Recurring topics across this work include Game Theory and Voting Systems (112 papers), Auction Theory and Applications (105 papers), Game Theory and Applications (38 papers), Complexity and Algorithms in Graphs (16 papers), Machine Learning and Algorithms (13 papers), Opinion Dynamics and Social Influence (10 papers), Logic, Reasoning, and Knowledge (9 papers) and Internet Traffic Analysis and Secure E-voting (9 papers). The work is most often cited by research in Management Science and Operations Research (2.2k citations), Economics and Econometrics (2.3k citations), General Decision Sciences (93 citations), Safety Research (410 citations) and Computational Theory and Mathematics (548 citations). Ariel D. Procaccia has collaborated with scholars based in United States, Israel and Greece. Frequent co-authors include Jeffrey S. Rosenschein, Nisarg Shah, Ioannis Caragiannis, Moshe Tennenholtz, Junxing Wang, David Kurokawa, David C. Parkes, Aviv Zohar, Ian A. Kash and Felix Fischer. Their work appears in journals such as Artificial Intelligence, Journal of Artificial Intelligence Research, Communications of the ACM, Operations Research and Autonomous Agents and Multi-Agent Systems.

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.

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