Category: Social Data Science
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In a world of “connective action” — what makes an influential Twitter user?
The new level of connectivity (particularly of social media) raises important questions about its role…
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Mapping Fentanyl Trades on the Darknet
The US accounts for almost 40% of global darknet trade, with Canada and Australia at…
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Our knowledge of how automated agents interact is rather poor (and that could be a problem)
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We might expect bot interactions to be relatively predictable and uneventful.
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Did you consider Twitter’s (lack of) representativeness before doing that predictive study?
Do Twitter users share identical characteristics with the population interest? For what populations are Twitter…
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Exploring the world of self-tracking: who wants our data and why?
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What happens when we turn our everyday experience—in particular, health and wellness-related experience—into data?
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Estimating the Local Geographies of Digital Inequality in Britain: London and the South East Show Highest Internet Use—But Why?
Britain has one of the largest Internet economies in the developed world, and the Internet…
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Edit wars! Examining networks of negative social interaction
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While these interactions are less common, they strongly affect people’s psychological well-being, physical health, and…
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Sexism Typology: Literature Review
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Drawing on the rich history of gender studies in the social sciences, coupling it with…
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Alan Turing Institute and OII: Summit on Data Science for Government and Policy Making
Leading policy makers, data scientists and academics came together to discuss how the ATI and…
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P-values are widely used in the social sciences, but often misunderstood: and that’s a problem.
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We need to make standards for interpreting p-values more stringent, and also improve transparency in…
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Facts and figures or prayers and hugs: how people with different health conditions support each other online
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Online support groups are one of the major ways in which the Internet has fundamentally…
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Topic modelling content from the “Everyday Sexism” project: what’s it all about?
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How does the topic modelling algorithm ‘discover’ the topics within the context of everyday sexism?