Developing Best Practices for Using Digital Tools to Study Human Behavior in Online Environments

  • Hargittai, Eszter (PD/PI)

Project: Research project

Project Details

Description

Much discussion and increasing resources have centered on big data opportunities to learn about human behavior mainly focusing on automatically-generated traces of people’s actions (e.g., Mayer-Schonberger & Cukier, 2013; National Science Foundation, 2012; Rosenbush & Totty, 2013). But so-called big data (e.g., behavioral trace data) also pose challenges from the politics that go into what data are generated and collected in the first place (Bowker, 2005; Gitelman, 2013), which are often not up to the researchers analyzing the data, to ethical considerations of what should be acceptable approaches to mining such data (boyd & Crawford, 2012). Moreover, fundamental methodological considerations about research design and sampling in such studies are often only addressed as an afterthought, if at all (Hargittai, Under review), ignoring crucial details about the generalizability of results derived from the analysis of big data. The goal of this project is to acknowledge, make visible, and address openly and head on the many challenges and opportunities of working with such vertical big data in the study of human behavior, and how digital tools can facilitate such processes. The workshop proposed in this project, the main focus of this planning grant, will bring together a dozen or so junior scholars embarking on related projects to discuss with each other and a group of senior scholars best practices for developing sharable, sustainable, and scalable approaches to collecting, coding, and analyzing such data that can also be compared across studies.
StatusFinished
Effective start/end date5/1/139/1/14

Funding

  • Alfred P. Sloan Foundation (BR2013-16)

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