Mitchell Joblin

19 papers receiving 305 citations

Peers

Mitchell Joblin
Comparison fields: 5 of 37
  • Computer Science Applications 118
  • Information Systems 168
  • Communication 29
  • Software 14
  • Artificial Intelligence 118
Replace Carlos Castro-Herrera with:
Carlos Castro-Herrera United States
Kris Cardinaels Belgium
Boris Wolf Germany
Sergey Chernov Finland
Changtao Qu Germany
Michael Meire Belgium
Tzone I. Wang Taiwan
Daniel Tunkelang United States
Philipp Heim Germany
Ralph R. Swick United States
Mitchell Joblin relative to Carlos Castro-Herrera United States Carlos Castro-Herrera's profile →
Citations per field
00.5×10×16.3×
Carlos Castro-Herrera · 1×
Citations per year

Countries citing papers authored by Mitchell Joblin

Since Specialization
Citations

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

Fields of papers citing papers by Mitchell Joblin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside Mitchell Joblin, 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 Mitchell Joblin Line = papers co-authored together Mitchell Joblin links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1 202272
2 201761
3 201540
4 201629
5 202024
6 202116
7 202313
8 202212
9 202210
10 20236
11 20226
12 20216
13 20214
14 20233
15 20213
16 20211
17 20161
18
A New Concept for Explaining Graph Neural Networks.
20211
19 20221

About Mitchell Joblin

Mitchell Joblin is a scholar working on Information Systems, Computer Science Applications, Artificial Intelligence, Statistical and Nonlinear Physics and Software, having authored 19 papers that have together received 309 indexed citations. Recurring topics across this work include Software Engineering Research (10 papers), Open Source Software Innovations (8 papers), Advanced Graph Neural Networks (4 papers), Software Engineering Techniques and Practices (4 papers), Topic Modeling (3 papers), Model-Driven Software Engineering Techniques (2 papers), Adversarial Robustness in Machine Learning (2 papers) and Complex Network Analysis Techniques (2 papers). The work is most often cited by research in Computer Science Applications (118 citations), Information Systems (168 citations), Communication (29 citations), Software (14 citations) and Artificial Intelligence (118 citations). Mitchell Joblin has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include Sven Apel, Wolfgang Mauerer, Marcel Hildebrandt, Yunpu Ma, Volker Tresp, Yushan Liu, Martin Ringsquandl, Dirk Riehle, Janet Siegmund and Damian A. Tamburri. Their work appears in journals such as ACM Transactions on Software Engineering and Methodology, Automated Software Engineering, Nature Communications, International Journal of Environmental Research and Public Health and Empirical Software Engineering.

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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