Join us as we explore how to describe trust, reputation and messiness using maths!
This week we're talking with Sean about how she translates the chaos of human relationships and interaction into precise, machine-readable descriptions. We learn why networks are useful for mapping out who (or what) is sharing information and building reputation.
Sean’s main interest lies in describing social phenomena with mathematical and computational concepts. Her current focus is on trust (interactions with potentially risky parties) and reputation (sharing opinions on how risky a party is). Primarily, she studies how delays in information sharing can be exploited by malicious parties and how to prevent this. Personal pages: https://se-si.github.io; https://www.cs.ox.ac.uk/people/sean.sirur
Recent papers: Properties of Reputation Lag Attack Strategies (2022, https://dl.acm.org/doi/abs/10.5555/3535850.3535985); Cooperation and distrust in extra-legal networks: a research note on the experimental study of marketplace disruption (2022, https://doi.org/10.1080/17440572.2022.2031152); Simulating the Impact of Personality on Fake News (2021, https://api.semanticscholar.org/CorpusID:244731942); The Reputation Lag Attack (2019, https://link.springer.com/chapter/10.1007/978-3-030-33716-2_4).