Big Data Meets Survey Science

Craig A. Hill, PhD, is Senior Vice President at RTI International and focuses on application of new technology to quantitative social science research. 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 6 other books published by Wiley.Trent D. Buskirk, PhD, 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.Lilli Japec, PhD, former Director of Research and Development Department at Statistics Sweden. She co-chaired AAPOR's Task Force on Big Data.Antje Kirchner, PhD, is a Survey Methodologist at RTI International. 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.Lars E. Lyberg, PhD, is former Head of the Research and Development Department at Statistics Sweden. He is the founder of the Journal of Official Statistics (JOS) and served as its Chief Editor for 25 years.

• Introduction (Hill, Biemer, Buskirk, Japec, Kirchner, Kolenikov, Lyberg)Section 1:  The New Survey Landscape1.            Why Machines Matter for Survey and Social Science Researchers: Exploring Applications of Machine Learning Methods for Design, Data Collection, and AnalysisTrent D. Buskirk and Antje Kirchner2.            The Future Is Now: How Surveys Can Harness Social Media To Address 21st Century ChallengesAmelia Burke-Garcia, Brad Edwards, and Ting Yan3.            Linking Survey Data with Commercial or Administrative Data for Data Quality AssessmentA.            Rupa Datta, Gabriel Ugarte, and Dean ResnickSection 2:  Total Error and Data Quality4.            Total Error Frameworks for Hybrid Estimation and Their ApplicationsPaul P. Biemer and Ashley Amaya5.            Measuring the Strength of Attitudes in Social Media DataaAshley Amaya, Ruben a, Frauke Kreuter, and Florian Keusch6.            Attention to Campaign Events: Do Twitter and Self-Report Metrics Tell the Same Story?Josh Pasek, Lisa O. Singh, Yifang Wei, Stuart N. Soroka, Jonathan M. Ladd, Michael W. Traugott, Ceren Budak, Leticia Bode, and Frank Newport7.            Improving Quality of Administrative Data: A Case Study with FBI’s National Incident-Based Reporting System DataDan Liao, Marcus Berzofsky, Lance Couzens, Ian Thomas, and Alexia Cooper8.            Performance and Sensitivities of Home Detection on Mobile Phone DataMaarten Vanhoof, Clement Lee, and Zbigniew SmoredaSection 3:  Big Data in Official Statistics9.            Big Data Initiatives in Official StatisticsLilli Japec and Lars Lyberg10.          Big Data in Official Statistics: A Perspective from Statistics NetherlandsBarteld Braaksma, Kees Zeelenberg, and Sofie De Broe11.          Mining the New Oil for Official StatisticsSiu-Ming Tam, J. K. Kim, Lyndon Ang, and Han Pham12.          Investigating Alternative Data Sources to Reduce Respondent Burden in United States Census Bureau Retail Economic Data ProductsRebecca J. HutchinsonSection 4:  Combining Big Data with Survey Statistics: Methods and Applications13.          Effects of Incentives in Smartphone Data CollectionGeorg-Christoph Haas, Frauke Kreuter, Florian Keusch, Mark Trappmann, and Sebastian Bähr14.          Using Machine Learning Models to Predict Attrition in a Survey PanelMingnan Liu15.          Assessing Community Well-being using Google Street-View and Satellite ImageryDr. Pablo Diego-Rosell, Stafford Nicols, Dr. Rajesh Srinivasan, and Dr. Ben Dilday16.          Nonparametric Bootstrap and Small Area Estimation to Mitigate Bias in Crowdsourced Data: Simulation Study and Application to Perceived SafetyDavid Buil-Gil, Reka Solymosi, and Angelo Moretti17.          Using Big Data to Improve Sample EfficiencyJamie Ridenhour, Joe McMichael, Karol Krotki, and Howard SpeizerSection 5:  Combining Big Data with Survey Statistics: Tools18.          Feedback Loop: Using Surveys to Build and Assess Registration-Based Sample Religious Flags for Survey ResearchDavid Dutwin19.          Artificial Intelligence and Machine Learning Derived Efficiencies for Large-Scale Survey Estimation EffortsSteven B. Cohen, PhD and Jamie Shorey, PhD20.          Worldwide Population Estimates for Small Geographic Areas: Can We Do a Better Job?Safaa Amer, Dana Thomson, Rob Chew, and Amy RoseSection 6:  The Fourth Paradigm, Regulations, Ethics, Privacy21.          Reproducibility in the Era of Big Data: Lessons for Developing Robust Data Management and Data Analysis ProceduresD.B. McCoach, J. Necci Dineen, Sandra M. Chafouleas, and Amy Briesch22.          Combining Active and Passive Mobile Data Collection: A Survey of ConcernsFlorian Keusch, Bella Struminskaya, Frauke Kreuter, and Martin Weichbold23.          Attitudes Toward Data Linkage: Privacy, Ethics, and the Potential for HarmAleia Clark Fobia, Jennifer Hunter Childs, and Casey Eggleston24.          Moving Social Science into the Fourth Paradigm: The Data Life CycleCraig A. Hill