Why Machines Matter for Survey and Social Science Researchers:
Exploring How Machine Learning Methods Can Be Applied to
the Design, Collection and Analysis of Social Science Data

Antje Kirchner, Ph.D.
Trent D. Buskirk, Ph.D.,

RTI International

Bowling Green State University

April 17th, 12-1 pm central time

$10 for students, $40 for non-student MAPOR members, $50 for non-members

Register here 

The exponential growth of computing power and cheap data storage have nourished artificial intelligence applications and machine learning methods to advance research in medicine, marketing, and many other fields. Despite the rising popularity, the potential of machine learning in survey and social science research has not yet been fully realized. This webinar provides an overview of how data science methods have been and can be applied to the social sciences from the perspective of the survey research process including: questionnaire design and evaluation; sampling; tailored survey designs and data collection; weighting adjustment and analysis. We illustrate how these methods can be used to augment, support, reimagine, improve and in some places replace the current methodologies. While machine learning is not likely to replace all human aspects of the survey research process, these methods offer new ways to approach traditional problems and have the potential to provide more efficiency, reduce errors, improve measurement and more cost-effective processing. We also discuss how errors in the machine learning process can impact errors we traditionally manage within the survey research process.

Recordings of the webinar will be available for those who cannot attend the event live. If interested, please register and you will receive a link to the recording after the event.

Register online at http://www.mapor.org/webinars/webinar-registration/