{"id":25625,"date":"2015-11-24T12:50:27","date_gmt":"2015-11-24T11:50:27","guid":{"rendered":"https:\/\/www.hiig.de\/en\/?p=25625"},"modified":"2023-06-02T12:34:20","modified_gmt":"2023-06-02T10:34:20","slug":"big-data-from-the-doom-of-sociology-to-its-method","status":"publish","type":"post","link":"https:\/\/www.hiig.de\/en\/big-data-from-the-doom-of-sociology-to-its-method\/","title":{"rendered":"Big data: from the doom of sociology to its method"},"content":{"rendered":"

This article was published first by the Internet Policy Review<\/a>.<\/em><\/p>\n

Once, Mike Savage predicted the downfall of sociology \u2013 but now, he revises his pessimism. In 2007, his famous essay \u201cThe coming crisis of empirical sociology\u201d had caused quite a stir. Back then, he stated that social scientists would be falling behind the natural scientists, failing to make use of the oil of the 21st century: big data.<\/p>\n

In a talk<\/a> within the series \u201cBig Data: Big power shifts?\u201d held on 5 November 2015 in Berlin, the sociologist from the London School of Economics and Political Sciences (LSE) drew the conclusion that, today, the most successful and popular social scientists primarily build up their work on data analysis.<\/p>\n

Today, it would be unthinkable that intellectuals could contrive theory buildings or propagate grand narratives like those of Michel Foucault or J\u00fcrgen Habermas. Still, there is a new star in the sky: the social scientist Thomas Piketty with his book \u201cCapital in the Twenty-First Century\u201d.<\/p>\n

Piketty as a pioneer of big data<\/h3>\n

Piketty is said to be using data from various sources, focusing on income distribution, in order to illustrate the complex coherences in a bunch of simple data visualisations. \u201cPiketty is using big Data, but he is not calling it Big Data,\u201d Savage said.<\/p>\n

Further, the French economist builds his critical reasoning on comprehensible data visualisations, combining a descriptive approach with critique regarding the prevailing conditions.<\/p>\n

Robert Putnam is said to be using a similar approach in his book \u201cBowling Alone\u201d, building his thesis of a decrease in social integration on data regarding memberships in clubs and other statistics. Another example for social sciences relying on big data is the book \u201cThe Spirit Level\u201d by Richard Wilkinson and Kate Pickett, which focuses on social inequality. According to Savage, social scientists are only able to make up for their lack of technical knowledge by a better contextualisation.<\/p>\n

At the 5 November event – organised by the Humboldt Institute for Internet and Society in collaboration with the Vodafone Institute for Society and Communications, Isabelle Sonnenfeld from Google News Lab made a similar statement: \u201cSocial scientists, unlike computer scientists, can come to a data source with a more complex and historical understanding.\u201d The group decided to make some of its most important data \u2013 search data \u2013 partially accessible via offerings such as google.com\/trends. But the decisive factor is not the data itself, but rather its interpretation. \u201cWe provide aggregated and anonymised Google Trends data, but it is the journalists and academics who are contextualising it,\u201d Sonnenfeld said.<\/p>\n