Publikation: Normalizing Digital Trace Data
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Gradually, over the last ten years, social scientists have found themselves confronting a massive increase in available data sources. The digitalization has, for example, opened up vast textual corpora (Grimmer & Stewart, 2013) and provided researchers with cheap and fast alternatives to telephone or face-to-face surveys (Callegaro, Manfreda, & Vehovar, 2015). Additionally, the growing use of digital services in everyday life provides social scientists with an ever increasing reservoir of digital data traces documenting slices of users’ everyday interactions with various digital devices or services (Howison, Wiggins, & Crowston, 2011). This increase in the variety and size of data available to researchers has been heralded by some as a measurement revolution for the social sciences (Golder & Macy, 2014; Lazer, Pentland, Adamic, Aral, Barabási, Brewer, Christakis, Contractor, Fowler, Gutmann, Jebara, King, Macy, Roy, & Van Alstyne, 2009; Schroeder, 2016; Watts, 2011). Especially, the research potential of digital trace data (Howison et al., 2011) has featured prominently in these accounts.
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JUNGHERR, Andreas, 2019. Normalizing Digital Trace Data. In: STROUD, Natalie Jomini, ed., Shannon C. MCGREGOR, ed.. Digital discussions : how big data informs political communication. New York, USA: Routledge : Taylor & Francis Group, 2019, pp. 9-35. ISBN 978-0-8153-8380-2BibTex
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title={Normalizing Digital Trace Data},
isbn={978-0-8153-8380-2},
publisher={Routledge : Taylor & Francis Group},
address={New York, USA},
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pages={9--35},
editor={Stroud, Natalie Jomini and McGregor, Shannon C.},
author={Jungherr, Andreas}
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