Lukasz Walasek

2.3k total citations
87 papers, 1.2k citations indexed

About

Lukasz Walasek is a scholar working on Clinical Psychology, Sociology and Political Science and Economics and Econometrics. According to data from OpenAlex, Lukasz Walasek has authored 87 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Clinical Psychology, 27 papers in Sociology and Political Science and 25 papers in Economics and Econometrics. Recurrent topics in Lukasz Walasek's work include Decision-Making and Behavioral Economics (22 papers), Gambling Behavior and Treatments (21 papers) and Behavioral Health and Interventions (11 papers). Lukasz Walasek is often cited by papers focused on Decision-Making and Behavioral Economics (22 papers), Gambling Behavior and Treatments (21 papers) and Behavioral Health and Interventions (11 papers). Lukasz Walasek collaborates with scholars based in United Kingdom, Australia and United States. Lukasz Walasek's co-authors include Gordon D. A. Brown, Neil Stewart, Sudeep Bhatia, Caroline Meyer, Philip Newall, Elliot A. Ludvig, Tim Rakow, Timothy L. Mullett, Nathaniel J. S. Ashby and William J. Matthews and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Psychological Bulletin and SHILAP Revista de lepidopterología.

In The Last Decade

Lukasz Walasek

78 papers receiving 1.2k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Lukasz Walasek United Kingdom 20 346 331 253 231 186 87 1.2k
Chiraag Mittal United States 9 302 0.9× 202 0.6× 358 1.4× 68 0.3× 106 0.6× 12 1.1k
David D. Loschelder Germany 20 558 1.6× 142 0.4× 331 1.3× 147 0.6× 84 0.5× 59 1.3k
Eesha Sharma United States 12 272 0.8× 139 0.4× 360 1.4× 93 0.4× 90 0.5× 22 977
Anja Achtziger Germany 18 376 1.1× 188 0.6× 359 1.4× 315 1.4× 124 0.7× 43 1.5k
Christopher J. Bryan United States 16 417 1.2× 198 0.6× 480 1.9× 95 0.4× 80 0.4× 25 1.5k
Sally Sadoff United States 15 183 0.5× 286 0.9× 161 0.6× 154 0.7× 278 1.5× 31 1.2k
John V. Petrocelli United States 20 547 1.6× 446 1.3× 530 2.1× 141 0.6× 49 0.3× 56 1.6k
N. S. Fagley United States 16 283 0.8× 246 0.7× 453 1.8× 441 1.9× 198 1.1× 35 1.5k
Noelle Nelson United States 6 234 0.7× 108 0.3× 290 1.1× 169 0.7× 56 0.3× 8 1.1k
Anya Samek United States 19 295 0.9× 91 0.3× 122 0.5× 186 0.8× 299 1.6× 88 1.2k

Countries citing papers authored by Lukasz Walasek

Since Specialization
Citations

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

Fields of papers citing papers by Lukasz Walasek

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lukasz Walasek

This figure shows the co-authorship network connecting the top 25 collaborators of Lukasz Walasek. A scholar is included among the top collaborators of Lukasz Walasek 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 Lukasz Walasek. Lukasz Walasek is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Bhatia, Sudeep, et al.. (2025). Computational analysis of 100 K choice dilemmas: Decision attributes, trade-off structures, and model-based prediction. Proceedings of the National Academy of Sciences. 122(17). e2406489122–e2406489122.
2.
Walasek, Lukasz, et al.. (2024). Attention-driven imitation in consumer reviews.. Decision. 11(4). 439–449. 1 indexed citations
3.
Bhatia, Sudeep & Lukasz Walasek. (2023). Predicting implicit attitudes with natural language data. Proceedings of the National Academy of Sciences. 120(25). e2220726120–e2220726120. 4 indexed citations
4.
Walasek, Lukasz, et al.. (2023). The Evolution of Polarization in Online Conversation: Twitter Users’ Opinions about the COVID-19 Pandemic Become More Politicized over Time. Human Behavior and Emerging Technologies. 2023. 1–14. 2 indexed citations
5.
Newall, Philip, et al.. (2023). Evaluation of the ‘take time to think’ safer gambling message: a randomised, online experimental study. Behavioural Public Policy. 9(4). 762–779. 12 indexed citations
6.
Singmann, Henrik, et al.. (2023). Replicability and reproducibility of predictive models for diagnosis of depression among young adults using Electronic Health Records. SHILAP Revista de lepidopterología. 7(1). 25–25. 2 indexed citations
7.
Meyer, Caroline, et al.. (2023). Prediction and diagnosis of depression using machine learning with electronic health records data: a systematic review. BMC Medical Informatics and Decision Making. 23(1). 271–271. 24 indexed citations
8.
Meyer, Caroline, et al.. (2023). Computational Analysis of Superfood Representations in News Media. Journal of Food Products Marketing. 29(8-9). 270–290. 2 indexed citations
9.
10.
Meyer, Caroline, et al.. (2022). Computational Methods for Predicting and Understanding Food Judgment. Psychological Science. 33(4). 579–594. 12 indexed citations
11.
Newall, Philip, Leonardo Weiss‐Cohen, Henrik Singmann, Lukasz Walasek, & Elliot A. Ludvig. (2022). Research Repository (Kingston University London). 38 indexed citations
12.
Walasek, Lukasz, et al.. (2022). Workplace inequality is associated with status-signaling expenditure. Proceedings of the National Academy of Sciences. 119(15). e2115196119–e2115196119. 6 indexed citations
13.
Newall, Philip, et al.. (2021). The stock market as a casino: Associations between stock market trading frequency and problem gambling. Journal of Behavioral Addictions. 10(3). 683–689. 19 indexed citations
14.
Walasek, Lukasz, Timothy L. Mullett, & Neil Stewart. (2021). Acceptance of mixed gambles is sensitive to the range of gains and losses experienced, and estimates of lambda (λ) are not a reliable measure of loss aversion: Reply to André and de Langhe (2021).. Journal of Experimental Psychology General. 150(12). 2666–2670. 2 indexed citations
15.
Walasek, Lukasz & Neil Stewart. (2020). You cannot accurately estimate an individual’s loss aversion using an accept–reject task.. Decision. 8(1). 2–15. 8 indexed citations
16.
Elliott, Mark T., et al.. (2019). Profiling Commenters on Mental Health–Related Online Forums: A Methodological Example Focusing on Eating Disorder–Related Commenters. JMIR Mental Health. 6(4). e12555–e12555. 11 indexed citations
17.
Walasek, Lukasz, et al.. (2019). Factors influencing employees' eating behaviours in the office‐based workplace: A systematic review. Obesity Reviews. 20(12). 1771–1780. 36 indexed citations
18.
Walasek, Lukasz & Neil Stewart. (2018). Context-dependent sensitivity to losses: Range and skew manipulations.. Journal of Experimental Psychology Learning Memory and Cognition. 45(6). 957–968. 20 indexed citations
19.
Walasek, Lukasz, et al.. (2018). Why do people reject mixed gambles. Cognitive Science. 1275–1281. 1 indexed citations
20.
Walasek, Lukasz & Neil Stewart. (2014). How to make loss aversion disappear and reverse: Tests of the decision by sampling origin of loss aversion.. Journal of Experimental Psychology General. 144(1). 7–11. 103 indexed citations

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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