Tomas Folke

971 citations
15 papers · 249 · h-index 8

Impact in

Papers in

    • Explainable Artificial Intelligence (XAI) 3
    • Adversarial Robustness in Machine Learning 2
    • Bayesian Modeling and Causal Inference 2
    • Psychological Well-being and Life Satisfaction 4

Tomas Folke

15 papers receiving 240 citations

Peers

Tomas Folke
Comparison fields: 5 of 79
  • General Decision Sciences 45
  • Health Informatics 8
  • Applied Psychology 25
  • Cognitive Neuroscience 100
  • Developmental and Educational Psychology 42
Replace Rachel Stephens with:
Rachel Stephens Australia
Eirik Strømland Norway
Brittany Shoots‐Reinhard United States
Eva M. Janssen Netherlands
Sébastien Massoni France
Brian R. Taylor United States
Timothy L. Mullett United Kingdom
Jane O’Connor United Kingdom
Kyle D. Dillon United States
Kinneret Teodorescu Israel
Tomas Folke relative to Rachel Stephens Australia Rachel Stephens's profile →
Citations per field
00.5×
Rachel Stephens · 1×
Citations per year

Countries citing papers authored by Tomas Folke

Since Specialization
Citations

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

Fields of papers citing papers by Tomas Folke

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 15 scholars most cited alongside Tomas Folke, 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 Tomas Folke Line = papers co-authored together Tomas Folke links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1 201683
2 201637
3 201922
4 202117
5 202015
6 202115
7 202013
8 202011
9 20227
10 20207
11 20215
12 20225
13 20235
14 20215
15 20212

About Tomas Folke

Tomas Folke is a scholar working on Artificial Intelligence, Social Psychology, Cognitive Neuroscience, Economics and Econometrics and General Decision Sciences, having authored 15 papers that have together received 249 indexed citations. Recurring topics across this work include Psychological Well-being and Life Satisfaction (4 papers), Decision-Making and Behavioral Economics (3 papers), Explainable Artificial Intelligence (XAI) (3 papers), Behavioral Health and Interventions (2 papers), Adversarial Robustness in Machine Learning (2 papers), Bayesian Modeling and Causal Inference (2 papers), Economic and Environmental Valuation (2 papers) and Experimental Behavioral Economics Studies (1 paper). The work is most often cited by research in General Decision Sciences (45 citations), Health Informatics (8 citations), Applied Psychology (25 citations), Cognitive Neuroscience (100 citations) and Developmental and Educational Psychology (42 citations). Tomas Folke has collaborated with scholars based in United States, United Kingdom and Netherlands. Frequent co-authors include Benedetto De Martino, Catrine Jacobsen, Stephen M. Fleming, Kai Ruggeri, Patrick Shafto, Scott Cheng‐Hsin Yang, Peter Bright, Roberto Filippi, Sanne E. Verra and Anatole Menon-Johansson. Their work appears in journals such as Health and Quality of Life Outcomes, Topics in Cognitive Science, Cognition, Nature Human Behaviour and Perspectives on Psychological Science.

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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