Big Data Meets Survey Science: A Collection of Innovative Methods - Rilegato

Rilegato

ISBN 10: 1118976320 ISBN 13: 9781118976326

Casa editrice: John Wiley & Sons Inc, 2020

Riassunto

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. 

Su questo libro

Informazioni sull?autore

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.

Dalla quarta di copertina

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.

Dettagli dell'edizione

• Editore: John Wiley & Sons Inc
• Data di pubblicazione: 2020
• Lingua: Inglese
• ISBN 10: 1118976320
• ISBN 13: 9781118976326
• Rilegatura: Copertina rigida
• Numero di pagine: 753
• Redattore: Hill Craig A., Biemer Paul P., Buskirk Trent D., Japec Lilli, Kirchner Antje
• Contatto del produttore: WROX; https://www.wiley.com/en-us; ; 111 River Street; Hoboken; NJ; 7030; U.S.A.
• Persona responsabile: non disponibile