Bev Skeggs on social media siloing

"Basically 90 percent of Facebook profit is made from advertising — selling your data to advertising companies so that they can place an advert on your browser..." says Bev Skeggs in a new interview with Social Science Bites. Bev Skeggs joins the podcast in order to reveal interesting new findings in her research that studies how social networks were structuring or restructuring friendships. 

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Big data rich and big data poor

Data is being created faster than ever before however without access to these data-sets or the expertise to analyse them, research is confronted with a replication crisis and is vulnerable to commercial motivations. The problem is growing as Katie Metzler points out, "Firstly, because replication is the engine of science, and irreproducible research slows progress... secondly the motivations of industry researchers and social scientists may differ in ways that may really matter." 

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Gary King: Do we need a big data treaty?

For years political scientist Gary King has argued and preached for a restructuring of the social sciences that would include “larger scale, collaborative, interdisciplinary, lab-style research teams” with big data analysis in their DNA. "The key reasons social sciences are moving from studying problems individually… to the scientific model where we’re actually solving problems, is because of the community. It is much easier to fool ourselves than it is to fool our community.” - Gary King

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Putting big data to good use

"Big data and mathematical models aren’t inherently bad... it depends on the way it’s used, by whom, and in service of what outcomes." says Katie Metzler. Against backdrop of media stories warning us about big data and its dangers, SAGE Publishing hosted a panel debate as part of the ESRC Festival of Social Science panel entitled  “Putting big data to good use” at the British Academy in London where Katie Metzler leads the discussion.

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How social media stymies social science

Getting data is becoming more and more of an issue and is unfortunately leading to consequences in academia. Disagreements that were usually solved with data are now getting lost due to the the little publicly available data on social media sites. This is a significant change to how social science researchers are gathering their data that professor Henry Farrell says is "badly understood."

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