Probabilistic modelling opinion formation in social interactions

advisor: Ing. Tatiana V. Guy, Ph.D.
e-mail: show e-mail
type: phd thesis
branch of study: MI_MM, MI_AMSM, MINF, APIN
key words: opinion formation; decision making; social interactions.
description: The social networks and online media irreversibly changed the way we become informed, and form our opinions [1]. Social networks are not organised via centralised decision making but through complex chain-like processes, where news items spread over different groups of members. Thus we observe a new phenomenon when agents (both humans and artificial ones) evaluate alternative opinions based on the opinions/judgements obtained from others (followers, friends, collaborators, etc.). High support of the favoured opinion in the social interaction is taken as a positive feedback that reinforces the value associated with this opinion. This phenomenon together with the constantly growing amount of circulating information catalyse different social effects: i) social exclusion and distrust [2]; ii) tendency to mimic the behaviour of other members [3]. In particular, echo chambers [2] quantified across different social networks have raised significant concerns on their potential impact on the spread of misinformation and on the overall behaviour of the social network. The proposed topic of PhD project aims at modelling opinion formation in social interactions by means of probabilistic modelling agents’ opinions as well as reinforcement mechanisms driving opinion change. Besides mostly theoretical insights into opinion formation process, the intended research could provide a solution how to stimulate transition from individual opinion to a consensus.
references: The literature will be gradually added based on the progress achieved. [1] Quattrociocchi W, Caldarelli G, Scala A. Opinion dynamics on interacting networks: media competition and social influence. Scientific reports. 2014; 4:4938. https://doi.org/10.1038/srep04938 [2] Nguyen, C., Echo chambers and epistemic bubbles, Episteme, 17(2), 2020. [3] Garcia, D. et al, Social resilience in online communities: The autopsy of friendster. Proc. COSN\'13, 2013. [4] Hahn, U. et al, How good is your evidence & how would you know? Top Cogn Sci, 10(4), 6, 2018. [5] M. H. DeGroot Optimal Statistical Decisions, Wiley 2004
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