Offers a clear view of the utility and place for survey data within the broader Big Data ecosystem
This book presents a collection of snapshots from two sides of the Big Data perspective. It assembles an array of tangible tools, methods, and approaches that illustrate how Big Data sources and methods are being used in the survey and social sciences to improve official statistics and estimates for human populations. It also provides examples of how survey data are being used to evaluate and improve the quality of insights derived from Big Data.
Big Data Meets Survey Science: A Collection of Innovative Methods shows how survey data and Big Data are used together for the benefit of one or more sources of data, with numerous chapters providing consistent illustrations and examples of survey data enriching the evaluation of Big Data sources. Examples of how machine learning, data mining, and other data science techniques are inserted into virtually every stage of the survey lifecycle are presented. Topics covered include: Total Error Frameworks for Found Data; Performance and Sensitivities of Home Detection on Mobile Phone Data; Assessing Community Wellbeing Using Google Street View and Satellite Imagery; Using Surveys to Build and Assess RBS Religious Flag; and more.
Presents groundbreaking survey methods being utilized today in the field of Big Data Explores how machine learning methods can be applied to the design, collection, and analysis of social science data Filled with examples and illustrations that show how survey data benefits Big Data evaluation Covers methods and applications used in combining Big Data with survey statistics Examines regulations as well as ethical and privacy issues
Big Data Meets Survey Science: A Collection of Innovative Methods is an excellent book for both the survey and social science communities as they learn to capitalize on this new revolution. It will also appeal to the broader data and computer science communities looking for new areas of application for emerging methods and data sources.
About the Author: Craig A. Hill, PhD is Senior Vice President at RTI International and has always had a research focus on application of new technology to quantitative social science research. He was the Chair of the Scientific Committee for the inaugural Big Data Meets Survey Science (BigSurv18) conference. He is also the lead editor of Social Media, Sociality, and Survey Research (Wiley, 2013).
Paul P. Biemer, PhD is Distinguished Fellow, Statistics at RTI International. He is an author, co-author and co-editor of other books including Introduction to Survey Quality, Latent Class Analysis of Survey Error, Measurement Errors in Surveys, Survey Measurement and Process Quality, Telephone Survey Methodology and Total Error in Practice, all published by John Wiley & Sons.
Trent D. Buskirk, Ph.D. is the Novak Family Distinguished Professor of Data Science and the Chair of the Applied Statistics and Operations Research Department in the College of Business at Bowling Green State University. Trent was the 2018 Conference chair of the American Association of Public Opinion Research and is a fellow of the American Statistical Association. His research interests include using technology to improve data collection and the application of data science methods to improve social science data collection, design and analysis.
Lilli Japec, Ph.D., former Director of Research and Development Department and Quality Director at Statistics Sweden. She co-chaired AAPOR's Task Force on Big Data and co-edited Advances in Telephone Survey Methodology published by John Wiley & Sons. Her main research interests include interview surveys, data quality and multiple data sources. Currently she serves as Senior Scientific Adviser at Statistics Sweden.
Antje Kirchner, Ph.D., is a Research Survey Methodologist at RTI International. Her work and research addresses challenges in survey methodology, for example, how to improve data quality using adaptive/responsive designs, or how to assess the quality of survey data leveraging new data sources. She is the Chair of the Scientific Committee of the "Big Data Meets Survey Science (BigSurv20)" conference.
Stanislav (Stas) Kolenikov, PhD, is Principal Scientist at Abt Associates. His work focuses on survey statistics, including issues in sampling, weighting, variance estimation, multiple imputation, and small area estimation; and on statistical computing, including software development and tools for reproducible workflows.
Lars E. Lyberg, Ph.D., is former Head of the Research and Development Department at Statistics Sweden and retired Professor at the Department of Statistics, Stockholm University. He is the founder of the Journal of Official Statistics (JOS) and served as its Chief Editor for 25 years. He is an author, co-author and co-editor of eight books all except one published by John Wiley & Sons. He currently serves as senior advisor at Demoskop, Inc.
