Megan Squire

58 total papers · 1.3k total citations
31 papers, 714 citations indexed

About

Megan Squire is a scholar working on Information Systems, Computer Science Applications and Communication. According to data from OpenAlex, Megan Squire has authored 31 papers receiving a total of 714 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Information Systems, 14 papers in Computer Science Applications and 8 papers in Communication. Recurrent topics in Megan Squire's work include Software Engineering Research (14 papers), Open Source Software Innovations (12 papers) and Scientific Computing and Data Management (7 papers). Megan Squire is often cited by papers focused on Software Engineering Research (14 papers), Open Source Software Innovations (12 papers) and Scientific Computing and Data Management (7 papers). Megan Squire collaborates with scholars based in United States, Germany and Sweden. Megan Squire's co-authors include Jeremy Blackburn, Jason Baumgartner, Savvas Zannettou, Brian Keegan, Daniel Schneider, James Howison, Daniel Izquierdo-Cortázar, Kevin Crowston, David Williams and Dugald Ralph Hutchings and has published in prestigious journals such as SHILAP Revista de lepidopterología, Empirical Software Engineering and Computers & composition.

In The Last Decade

Megan Squire

31 papers receiving 685 citations

Hit Papers

The Pushshift Reddit Dataset 2020 2026 2022 2024 2020 100 200 300 400

Author Peers

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

Author Last Decade Papers Cites
Megan Squire 319 205 203 164 98 31 714
Ruogu Kang 178 0.6× 214 1.0× 332 1.6× 129 0.8× 94 1.0× 18 643
Zhe Liu 413 1.3× 171 0.8× 173 0.9× 76 0.5× 85 0.9× 15 669
José San Pedro 237 0.7× 206 1.0× 152 0.7× 63 0.4× 49 0.5× 20 673
Karin Becker 316 1.0× 236 1.2× 211 1.0× 126 0.8× 58 0.6× 110 811
Saiph Savage 187 0.6× 106 0.5× 368 1.8× 98 0.6× 230 2.3× 47 888
Sanjay Kairam 198 0.6× 188 0.9× 263 1.3× 157 1.0× 101 1.0× 23 688
Georg Groh 367 1.2× 239 1.2× 146 0.7× 105 0.6× 21 0.2× 93 843
Dominic DiFranzo 347 1.1× 136 0.7× 270 1.3× 123 0.8× 23 0.2× 34 723
Dario Taraborelli 155 0.5× 242 1.2× 118 0.6× 200 1.2× 82 0.8× 25 746
Aaron Hoff 194 0.6× 170 0.8× 414 2.0× 185 1.1× 44 0.4× 14 797

Countries citing papers authored by Megan Squire

Since Specialization
Citations

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

Fields of papers citing papers by Megan Squire

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Megan Squire

This figure shows the co-authorship network connecting the top 25 collaborators of Megan Squire. A scholar is included among the top collaborators of Megan Squire 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 Megan Squire. Megan Squire 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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