Oleksandr Pryymak

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In this paper we present an approach for improving the accuracy of shared opinions in a large decentralised team. Specifically, our solution optimises the opinion sharing process in order to help the majority of agents to form the correct opinion about a state of a common subject of interest, given only few agents with noisy sensors in the large team. We(More)
In this paper, we are interested in understanding the interrelationships between mainstream and social media in forming public opinion during mass crises, specifically in regards to how events are framed in the mainstream news and on social networks and to how the language used in those frames may allow to infer political slant and partisanship. We study(More)
In large decentralised teams agents often share uncertain and conflicting information across the network, and it is a major challenge for team members to reach accurate conclusions individually. Previously, this problem was approached by introducing a communication overhead in order to reason about the accuracy of information or to reach agreements(More)
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