Tim Donkers

5 papers and 21 indexed citations i.

About

Tim Donkers is a scholar working on Artificial Intelligence, Information Systems and Safety Research. According to data from OpenAlex, Tim Donkers has authored 5 papers receiving a total of 21 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 4 papers in Information Systems and 1 paper in Safety Research. Recurrent topics in Tim Donkers’s work include Recommender Systems and Techniques (4 papers), Advanced Graph Neural Networks (2 papers) and Topic Modeling (2 papers). Tim Donkers is often cited by papers focused on Recommender Systems and Techniques (4 papers), Advanced Graph Neural Networks (2 papers) and Topic Modeling (2 papers). Tim Donkers collaborates with scholars based in Germany. Tim Donkers's co-authors include Jürgen Ziegler and Benedikt Loepp and has published in prestigious journals such as International Journal of Human-Computer Studies, i-com and Conference on Recommender Systems.

In The Last Decade

Co-authorship network of co-authors of Tim Donkers i

Fields of papers citing papers by Tim Donkers

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Tim Donkers

Since Specialization
Citations

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

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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2025