Michael Siebers

481 citations
27 papers · 197 · h-index 8

Impact in

    • Vaccine Coverage and Hesitancy
    • Gun Ownership and Violence Research
    • Behavioral Health and Interventions

Papers in

Michael Siebers

21 papers receiving 189 citations

Peers

Michael Siebers
Comparison fields: 5 of 83
  • Health 26
  • Applied Psychology 9
  • Information Systems and Management 13
  • Pharmacology 29
  • Experimental and Cognitive Psychology 23
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Citations per field
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Citations per year

Countries citing papers authored by Michael Siebers

Since Specialization
Citations

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

Fields of papers citing papers by Michael Siebers

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Michael Siebers, 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 Michael Siebers Line = papers co-authored together Michael Siebers links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202139
2 201537
3 198527
4 202221
5 200814
6 20188
7 19978
8 20197
9 20155
10 19925
11 20175
12 20174
13
Analogical Problem Solving: Insights from Verbal Reports
20123
14 20193
15
Applying Grammar Inference To Identify Generalized Patterns of Facial Expressions of Pain
20122
16 20171
17 20111
18
Intentionales Vergessen im Arbeitsalltag : Eine Critical Incident Untersuchung
20171
19 20101
20
Forgetting in future work systems: System characteristics and user-related psychological consequences on emotion, cognition, and behaviors
20181

About Michael Siebers

Michael Siebers is a scholar working on Artificial Intelligence, Experimental and Cognitive Psychology, Computer Vision and Pattern Recognition, Information Systems and Management and Pharmacology, having authored 27 papers that have together received 197 indexed citations. Recurring topics across this work include AI-based Problem Solving and Planning (4 papers), Face and Expression Recognition (3 papers), Explainable Artificial Intelligence (XAI) (3 papers), Cognitive Functions and Memory (2 papers), Computability, Logic, AI Algorithms (2 papers), Cannabis and Cannabinoid Research (2 papers), Teaching and Learning Programming (2 papers) and Data Stream Mining Techniques (2 papers). The work is most often cited by research in Health (26 citations), Applied Psychology (9 citations), Information Systems and Management (13 citations), Pharmacology (29 citations) and Experimental and Cognitive Psychology (23 citations). Michael Siebers has collaborated with scholars based in Germany, United States and Australia. Frequent co-authors include Ute Schmid, Sarah V. Biedermann, Johannes Fuß, Beat Lutz, Laura Bîndilă, José Hernández‐Orallo, David L. Dowe, Fernando Martínez‐Plumed, Cornelia Niessen and Carey E. Gleason. Their work appears in journals such as Journal of the American Geriatrics Society, Frontiers in Physiology, European Psychiatry, Psychoneuroendocrinology and The Neuroscientist.

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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