Promises and Pitfalls of Using Digital Traces for Demographic Research

27 Pages Posted: 20 Sep 2016 Last revised: 17 Mar 2018

See all articles by Nina Cesare

Nina Cesare

University of Washington - Sociology

Hedwig Lee

University of Washington

Tyler McCormick

Columbia University - Department of Statistics

Emma Spiro

University of Washington - The Information School; University of Washington - Sociology

Emilio Zagheni

University of Washington - Department of Sociology

Date Written: September 15, 2016

Abstract

The digital traces we leave online are increasingly fruitful sources of data for social scientists - including those interested in demographic research. The collection and use of digital data also presents numerous statistical, computational, and ethical challenges, motivating the development of new research approaches to address these burgeoning issues. In this article, we argue that researchers with formal training in demography – who have a history of developing innovative approaches to using challenging data – are well positioned to contribute to this area of work. We discuss the benefits and challenges of using digital trace data for social and demographic research, and review examples of current demographic literature that creatively utilizes digital trace data to study processes related to fertility, mortality and migration. Focusing on Facebook data for advertisers –a novel, ‘digital census’ that has largely been untapped by demographers – we provide illustrative and empirical examples of how demographic researchers can manage issues such as bias and representation when using digital trace data. We conclude by offering our perspective on the road ahead regarding demography and its role in the ‘data revolution.’

Keywords: Digital data, social media, big data, demographic methods

Suggested Citation

Cesare, Nina and Lee, Hedwig and McCormick, Tyler and Spiro, Emma and Zagheni, Emilio, Promises and Pitfalls of Using Digital Traces for Demographic Research (September 15, 2016). Available at SSRN: https://ssrn.com/abstract=2839585 or http://dx.doi.org/10.2139/ssrn.2839585

Nina Cesare (Contact Author)

University of Washington - Sociology ( email )

Seattle, WA 98195
United States

Hedwig Lee

University of Washington ( email )

Seattle, WA 98195
United States

Tyler McCormick

Columbia University - Department of Statistics ( email )

Mail Code 4403
New York, NY 10027
United States

Emma Spiro

University of Washington - The Information School ( email )

Box 353350
Seattle, WA 98195
United States

University of Washington - Sociology ( email )

Seattle, WA 98195
United States

Emilio Zagheni

University of Washington - Department of Sociology ( email )

Seattle, WA 98195
United States

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