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Dr Paul Rauwolf

Lecturer

p.rauwolf@bangor.ac.uk

+44 1248 388680

0000-0002-4715-8644

Dr Paul Rauwolf

View Dr Paul Rauwolf’s profile on the Bangor Research Portal

Additional Contact Information

Email: p.rauwolf@bangor.ac.uk

Office: 368 Brigantia building

Postgraduate Project Opportunities

Self-funded (inc. agency-funded) projects: Dr. Rauwolf welcomes informal enquiries from prospective PhD students interested in projects related to several aspects of human decision-making and coopeartion, including: decision-making biases, decision-making under uncertainty, social decision-making in cooperative contexts, and misinformation in social media / online outlets. Please submit a draft research proposal (1-2 pages) to the above email address.

Competitive scholarship opportunities available: 

A fully-funded studentship is being offered to better understand how individuals learn in uncertain, social environments. This will involve testing how individuals act in various types of social settings when interacting in a social dilemma. Participants will interact with various types of computer partners who will operate with particular social norms. We will manipulate the strategies of the computer partners in the social dilemma to find which kinds of social norms best enable individuals to socially learn how to navigate a collective action problem.

For full information please go to: Fully-funded PhD Studentship: Learning in uncertain and social environments (bangor.ac.uk)

Publications

2022

  • PublishedInterpersonal factors and mental well-being are associated with accuracy in judging the veracity of political news
    Rauwolf, P., May 2022, In: Applied Cognitive Psychology. 36, 3, p. 581-601 21 p.
    Research output: Contribution to journal › Article › peer-review

2021

  • Published'Just not knowing' can make life sweeter (and saltier): Reward uncertainty alters the sensory experience and consumption of palatable food and drinks
    Rauwolf, P., Mallard, S., Wong, N., Witt, A., Davies, T., Cahill, A., Madden, G. J., Parkinson, J. & Rogers, R., Oct 2021, In: Journal of Experimental Psychology: General. 150, 10, p. 2015-2035
    Research output: Contribution to journal › Article › peer-review

2020

  • PublishedEvolutionary Psychology and Artificial Intelligence: The Impact of Artificial Intelligence on Human Behaviour
    Wilson, H., Rauwolf, P. & Bryson, J. J., 25 Nov 2020, The SAGE Handbook of Evolutionary Psychology: Applications of Evolutionary Psychology. 1 ed. London, p. 333-351 19 p.
    Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review
  • PublishedHostility is associated with self-reported cognitive and social benefits across Massively Multiplayer Online Role-Playing Game player-roles
    Smith, C. M., Rauwolf, P., Intriligator, J. & Rogers, R. D., Jul 2020, In: Cyberpsychology, Behavior, and Social Networking. 23, 7, p. 487-494
    Research output: Contribution to journal › Article › peer-review

2019

  • PublishedExploring the utility of internal whistleblowing in healthcare via agent-based models
    Rauwolf, P. & Jones, A., 25 Jan 2019, In: BMJ Open. 9, 1, e021705.
    Research output: Contribution to journal › Article › peer-review

2018

  • PublishedExpectations of Fairness and Trust Co-Evolve in Environments of Partial Information
    Rauwolf, P. & Bryson, J., Dec 2018, In: Dynamic Games and Applications. 8, 4, p. 891-917
    Research output: Contribution to journal › Article › peer-review

2016

  • PublishedOn the reliability of unreliable information Gossip as cultural memory
    Mitchell, D., Bryson, J. J., Rauwolf, P. & Ingram, G. P. D., Jan 2016, In: Interaction Studies. 17, 1, p. 1-18
    Research output: Contribution to journal › Article › peer-review

2015

  • PublishedValue homophily benefits cooperation but motivates employing incorrect social information
    Rauwolf, P., Mitchell, D. & Bryson, J. J., 21 Feb 2015, In: Journal of Theoretical Biology. 367, p. 246-261
    Research output: Contribution to journal › Article › peer-review

Projects

  • Understanding the psychological risk factors for believing political misinformation by merging neural network and multiple regression models

    28/01/2022 – 31/03/2023 (Finished)

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