Toby D. Pilditch

2.1k total citations
27 papers, 293 citations indexed

About

Toby D. Pilditch is a scholar working on Artificial Intelligence, Sociology and Political Science and Statistical and Nonlinear Physics. According to data from OpenAlex, Toby D. Pilditch has authored 27 papers receiving a total of 293 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 9 papers in Sociology and Political Science and 8 papers in Statistical and Nonlinear Physics. Recurrent topics in Toby D. Pilditch's work include Opinion Dynamics and Social Influence (8 papers), Misinformation and Its Impacts (6 papers) and Decision-Making and Behavioral Economics (5 papers). Toby D. Pilditch is often cited by papers focused on Opinion Dynamics and Social Influence (8 papers), Misinformation and Its Impacts (6 papers) and Decision-Making and Behavioral Economics (5 papers). Toby D. Pilditch collaborates with scholars based in United Kingdom, Netherlands and Australia. Toby D. Pilditch's co-authors include Jens Koed Madsen, David A. Lagnado, Norman Fenton, Ulrike Hahn, Richard M. Bailey, Ruud Custers, Наоми Орескес, Stephan Lewandowsky, James S. Risbey and Martin Neil and has published in prestigious journals such as PLoS ONE, Scientific Reports and Psychological Science.

In The Last Decade

Toby D. Pilditch

27 papers receiving 281 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Toby D. Pilditch United Kingdom 11 155 71 47 44 38 27 293
Brian Guay United States 6 248 1.6× 42 0.6× 66 1.4× 24 0.5× 23 0.6× 11 321
Michael N. Stagnaro United States 10 287 1.9× 32 0.5× 40 0.9× 76 1.7× 86 2.3× 23 429
Patrizia Milesi Italy 11 202 1.3× 15 0.2× 22 0.5× 92 2.1× 64 1.7× 21 316
Tzur M. Karelitz United States 9 98 0.6× 11 0.2× 56 1.2× 39 0.9× 26 0.7× 18 345
Ian Anderson United States 6 162 1.0× 19 0.3× 36 0.8× 21 0.5× 14 0.4× 8 235
Sebastian Bobadilla-Suarez United Kingdom 6 88 0.6× 9 0.1× 21 0.4× 40 0.9× 111 2.9× 8 256
Daniel Geschke Germany 8 267 1.7× 51 0.7× 28 0.6× 89 2.0× 32 0.8× 12 357
Andrew J. W. Civettini United States 4 268 1.7× 25 0.4× 33 0.7× 50 1.1× 21 0.6× 4 357
Madalina Vlasceanu United States 11 206 1.3× 28 0.4× 31 0.7× 32 0.7× 65 1.7× 31 292
Fabian Winter Germany 9 173 1.1× 9 0.1× 36 0.8× 43 1.0× 40 1.1× 34 287

Countries citing papers authored by Toby D. Pilditch

Since Specialization
Citations

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

Fields of papers citing papers by Toby D. Pilditch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Toby D. Pilditch. 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 Toby D. Pilditch. The network helps show where Toby D. Pilditch may publish in the future.

Co-authorship network of co-authors of Toby D. Pilditch

This figure shows the co-authorship network connecting the top 25 collaborators of Toby D. Pilditch. A scholar is included among the top collaborators of Toby D. Pilditch 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 Toby D. Pilditch. Toby D. Pilditch 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.
Pilditch, Toby D., Ulrike Hahn, & David A. Lagnado. (2025). The problem of dependency. Synthese. 205(4). 1 indexed citations
2.
Madsen, Jens Koed, et al.. (2024). Modelling Adaptive and Anticipatory Human Decision-Making in Complex Human-Environment Systems. Journal of Artificial Societies and Social Simulation. 27(1). 2 indexed citations
3.
Madsen, Jens Koed, Ulrike Hahn, & Toby D. Pilditch. (2020). The impact of partial source dependence on belief and reliability revision.. Journal of Experimental Psychology Learning Memory and Cognition. 46(9). 1795–1805. 15 indexed citations
4.
Pilditch, Toby D., et al.. (2020). Strange but true: Corroboration and base rate neglect.. Journal of Experimental Psychology Learning Memory and Cognition. 47(1). 11–28. 2 indexed citations
5.
Pilditch, Toby D., et al.. (2020). Strategies for selecting and evaluating information. Cognitive Psychology. 123. 101332–101332. 7 indexed citations
6.
Pilditch, Toby D., Ulrike Hahn, Norman Fenton, & David A. Lagnado. (2020). Dependencies in evidential reports: The case for informational advantages. Cognition. 204. 104343–104343. 13 indexed citations
7.
Pilditch, Toby D., et al.. (2019). Zero-sum reasoning in information selection.. Cognitive Science. 938–943. 1 indexed citations
8.
Madsen, Jens Koed, Ulrike Hahn, & Toby D. Pilditch. (2019). Reasoning about dissent: Expert disagreement and shared backgrounds.. Cognitive Science. 2228–2234. 1 indexed citations
9.
Pilditch, Toby D., Ulrike Hahn, & David A. Lagnado. (2019). Shared Evidence: It all depends.... Cognitive Science. 2571–2577. 1 indexed citations
10.
Pilditch, Toby D., Jens Koed Madsen, & Ruud Custers. (2019). False prophets and Cassandra's curse: The role of credibility in belief updating. Acta Psychologica. 202. 102956–102956. 17 indexed citations
11.
Lewandowsky, Stephan, Toby D. Pilditch, Jens Koed Madsen, Наоми Орескес, & James S. Risbey. (2019). Influence and seepage: An evidence-resistant minority can affect public opinion and scientific belief formation. Cognition. 188. 124–139. 35 indexed citations
12.
Madsen, Jens Koed, Ulrike Hahn, & Toby D. Pilditch. (2018). Partial source dependence and reliability revision: the impact of shared backgrounds.. Cognitive Science. 5 indexed citations
13.
Pilditch, Toby D., David A. Lagnado, & Ulrike Hahn. (2018). Integrating dependent evidence: naïve reasoning in the face of complexity. Cognitive Science. 3 indexed citations
14.
Pilditch, Toby D., et al.. (2018). Evaluating testimony from multiple witnesses: single cue satisficing or integration?. Cognitive Science. 3 indexed citations
15.
Madsen, Jens Koed & Toby D. Pilditch. (2018). A method for evaluating cognitively informed micro-targeted campaign strategies: An agent-based model proof of principle. PLoS ONE. 13(4). e0193909–e0193909. 12 indexed citations
16.
Osman, Magda, Norman Fenton, Toby D. Pilditch, David A. Lagnado, & Martin Neil. (2018). Whom Do We Trust on Social Policy Interventions?. Basic and Applied Social Psychology. 40(5). 249–268. 25 indexed citations
17.
Madsen, Jens Koed, Richard M. Bailey, & Toby D. Pilditch. (2018). Large networks of rational agents form persistent echo chambers. Scientific Reports. 8(1). 12391–12391. 39 indexed citations
18.
Pilditch, Toby D.. (2017). Opinion Cascades and Echo-Chambers in Online Networks: A Proof of Concept Agent-Based Model. Cognitive Science. 5 indexed citations
19.
Madsen, Jens Koed, Richard M. Bailey, & Toby D. Pilditch. (2017). Growing a Bayesian Conspiracy Theorist: An Agent-Based Model. Cognitive Science. 2 indexed citations
20.
Pilditch, Toby D. & Ruud Custers. (2017). Communicated beliefs about action-outcomes: The role of initial confirmation in the adoption and maintenance of unsupported beliefs. Acta Psychologica. 184. 46–63. 11 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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