February 2023 – Big Data – Big Deal or Bigger Deal Breaker
In 2023, WAPOR resumes our education program with a new series of webinars on public opinion research methodology. Our first webinar will take place on Friday, February 24 at 10.00-11.30 AM EST. Our excellent speaker, Professor Trent D. Buskirk will deliver a talk on “Big Data – Big Deal or Bigger Deal Breaker: Sifting through the hype to uncover quality and conundrums with modern data sources“. Attendance is free of charge; WAPOR membership is not required. Gary Langer (Langer Research Associates, USA), WAPOR Education Committee member, will moderate the discussion.
Slides: Big Data – Big Deal or Bigger Deal Breaker: PPT SLIDES
Video: Big Data – Big Deal or Bigger Deal Breaker: VIDEO
Big Data – Big Deal or Bigger Deal Breaker: Sifting through the hype to uncover quality and conundrums with modern data sources
With survey research participation declining and costs rising, researchers and practitioners alike are exploring and using new and alternate sources of data for measuring public opinion. As the array of data types continues to diversify and access to such information becomes easier and cheaper, researchers are faced with real decisions around fitness for purpose and in balancing cost with data quality and availability. And while much of the literature discussed downplays the hype in these alternate data sources, some hype up their use as complete alternatives to the status quo. In this talk we take a deeper dive into both the potential and possible perils of using various new types of big data for measuring public opinion and behavioral outcomes. In particular we will define and explore specific types of big data including: administrative data, digital trace data, social media data and sensor data. While no prior knowledge of these big data sources are assumed, some familiarity with the survey research process would be helpful as we seek to place the use of these new data types within the context of survey research. Participants will learn how each of these new data types are defined and where they may be accessed as well as taking away a balanced view of when or how this type of information could be leveraged for understanding public opinion and behavioral outcomes within their own research and practice.
Trent D. Buskirk
Trent D. Buskirk, PhD is the Novak Family Distinguished Professor of Data Science and outgoing Chair of the Applied Statistics and Operations Research Department at Bowling Green State University. Dr. Buskirk is a Fellow of the American Statistical Association and his research interests include big data quality, recruitment methods through social media, the use of big data and machine learning methods for health, social and survey science design and analysis, mobile and smartphone survey designs and in methods for calibrating and weighting nonprobability samples and fairness in AI models and interpretable ML methods. Recently, Trent served as the President of the Midwest Association for Public Opinion Research in 2016, the Conference Chair for AAPOR in 2018 and is currently part of the scientific committee for the BigSurv23 conference. Trent also serves as an Associate Editor for Methods for the Journal of Survey Statistics and Methodology. When Trent is not geeking out over big data and survey methods you can find him playing a competitive game of Pickleball!