Mads Haahr

110 total papers · 2.6k total citations
42 papers, 1.6k citations indexed

About

Mads Haahr is a scholar working on Computer Networks and Communications, Computer Vision and Pattern Recognition and Sociology and Political Science. According to data from OpenAlex, Mads Haahr has authored 42 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Computer Networks and Communications, 11 papers in Computer Vision and Pattern Recognition and 9 papers in Sociology and Political Science. Recurrent topics in Mads Haahr's work include Peer-to-Peer Network Technologies (9 papers), Digital Games and Media (6 papers) and Educational Games and Gamification (6 papers). Mads Haahr is often cited by papers focused on Peer-to-Peer Network Technologies (9 papers), Digital Games and Media (6 papers) and Educational Games and Gamification (6 papers). Mads Haahr collaborates with scholars based in Ireland, United Kingdom and United States. Mads Haahr's co-authors include Elizabeth Daly, Alan Gray, Raymond Cunningham, Vinny Cahill, Niamh C. Nowlan, Pádraig Cunningham, Sarah Jane Delany, Katsiaryna Naliuka, Barbara De Kegel and Atul Singh and has published in prestigious journals such as Communications of the ACM, Journal of Sports Sciences and IEEE Transactions on Mobile Computing.

In The Last Decade

Mads Haahr

37 papers receiving 1.5k citations

Hit Papers

Social network analysis f... 2007 2026 2013 2019 2007 2008 250 500 750

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Mads Haahr 1.3k 205 184 152 137 42 1.6k
Tristan Henderson 1.4k 1.1× 191 0.9× 260 1.4× 329 2.2× 481 3.5× 76 2.0k
Shivakant Mishra 1.1k 0.8× 448 2.2× 704 3.8× 70 0.5× 202 1.5× 111 2.0k
Stephen Farrell 1.3k 1.0× 322 1.6× 160 0.9× 31 0.2× 265 1.9× 70 1.8k
Oliver Brdiczka 598 0.5× 402 2.0× 406 2.2× 98 0.6× 154 1.1× 46 1.6k
Doug Terry 1.5k 1.2× 541 2.6× 183 1.0× 40 0.3× 104 0.8× 34 1.8k
Cristian Borcea 1.0k 0.8× 180 0.9× 181 1.0× 257 1.7× 720 5.3× 94 1.7k
Polly Huang 1.2k 0.9× 94 0.5× 161 0.9× 29 0.2× 580 4.2× 68 1.8k
Benjamin Lee 663 0.5× 185 0.9× 141 0.8× 18 0.1× 181 1.3× 35 1.5k
Mike Perkowitz 554 0.4× 834 4.1× 580 3.2× 90 0.6× 184 1.3× 19 1.8k
Mohan Kumar 1.3k 1.0× 367 1.8× 191 1.0× 69 0.5× 216 1.6× 91 1.6k

Countries citing papers authored by Mads Haahr

Since Specialization
Citations

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

Fields of papers citing papers by Mads Haahr

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mads Haahr. 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 Mads Haahr. The network helps show where Mads Haahr may publish in the future.

Co-authorship network of co-authors of Mads Haahr

This figure shows the co-authorship network connecting the top 25 collaborators of Mads Haahr. A scholar is included among the top collaborators of Mads Haahr 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 Mads Haahr. Mads Haahr is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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