UX Researcher | Behavioural Scientist | Forbes 30 Under 30 Europe
Dr Vyacheslav Polonski, who often goes by the name Slava, is a UX Researcher at Google. He specialises in human-centred machine learning and is a Founding Fellow of Google’s People+AI Guidebook. Previously, he was a researcher at the Oxford Internet Institute (OII), studying complex social networks, user behaviour and technology adoption. In 2017, Vyacheslav completed his PhD studies at the University of Oxford as an ESRC Scholar. Prior to his PhD, Vyacheslav completed an MSc in the Social Sciences of the Internet at the OII and a BSc in Management at LSE. Vyacheslav is an active member of the World Economic Forum having participated in multiple conferences as a Global Shaper (2015, 2016, 2017) and member of the WEF Expert Network (2017, 2018). He co-founded Avantgarde Analytics, a machine learning startup that harnessed AI & behavioural psychology for algorithmic campaigning. In 2018, Forbes Magazine featured him in the 30 Under 30 list. His research and commentary have been highlighted in the media, including in The Independent, Forbes, Bloomberg, TechCrunch, Scientific American and The New York Times.
University of Oxford / Harvard University
Ph.D (D.Phil) in Computational Social Science at Oxford Internet Institute
Visiting Fellow at Harvard Graduate School of Arts and Sciences
University of Oxford
M.Sc in Social Science of the Internet (Distinction)
London School of Economics
B.Sc in Management (First Class Honours)
Undergraduate of the Year 2012
Areas of EXPERTISE
Mapping political polarisation on social media
The Internet has rewired civil society, propelling collective action to a new dimension of citizen autonomy. Yet it has also contributed to radicalisation and conflict. As part of a larger study on the future of digital democracy, I have analysed large amounts of social media data to understand how political polarisation on social media has fuelled the rise of populism with regard to the Brexit vote in the UK's recent EU referendum and its implications for future elections.
Analysing the network structure of online communities
Global Shapers Community
Social network analysis provides a large toolkit of quantitative techniques that allow us to understand the structure of relationships of people in the context of their social groups. Using these tools, I have analysed the friendship relationships and conversational patterns of the World Economic Forum's Global Shapers Community, which spans across 450 hubs and brings together young people to work on social impact projects in their cities.
Exploring the spread of ideas in semantic networks
World Economic Forum
Ideas and concepts that are related to each other can be visualised in semantic networks that represent the degree of connection between these concepts, e.g. to understand the degree of relatedness of meanings associated with individuals, places or entities. Having extracted hashtags from Instagram activities around the WEF Annual Meeting in Davos 2016, I have looked at the way how the event was perceived and experienced by its participants and the general public.