This topical collection “Integrating Survey and Non-survey Data to Measure Behavior and Public Opinion” follows a very successful Big Data Meets Survey Science (BigSurv20) virtual conference, in 2020. The overall goal of the BigSurv series of conferences addresses the growing reality that surveys are no longer the single, primary source for (official) statistics or public opinion. The growing penetration of both internet service and smartphones have led to new streams of data collected through meters, sensors, and apps. These alternative data sources and with them big data analytics have started to permeate different parts of scientific inquiry ranging from study design, and sampling design to data processing and estimation allowing us to better measure behavior and public opinion.
In this collection we present some state-of-the-art research at the intersection of survey and non-survey data for data collection and analyses, exploring important issues pertaining to their combination and use in the social and data sciences. Relevant topics center around the combination and integration of survey data and alternative data sources, often a by-product of our increasingly digital lives, ranging from social media data, sensor data, to app data. While the work at combining surveys, big data and data science continues to emerge, we believe the articles in this special issue begin to lay the groundwork for a new era of survey data science in which best current practices and approaches demonstrated here will continue to develop and evolve into more systematic and widespread approaches.
Lead Guest Editor:
Antje Kirchner, RTI International, University of Nebraska - Lincoln, USA
Trent Buskirk, Bowling Green State University, USA
Ingmar Weber, Hamad Bin Khalifa University, Doha, Qatar
Nan Zhang, American University, USA