Abstract
User-centric behavioral tracking, a cutting-edge computational social science tool, holds tremendous promise for advertising research. The article introduces the technique and presents three do-it-yourself (DIY) case studies in which researchers develop tracking applications and platforms, build infrastructures that host participants, maintain computational pipelines logging user behavior and content exposure, and manage logistical “ins and outs” such as onboarding, offboarding, and compensations all by themselves. We share our lessons, discuss challenges ahead for DIY user-centric behavioral tracking, and advocate for computational advertising scholars to become pioneers in this emerging body of work.
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