Bit by Bit (eBook)

Social Research in the Digital Age
eBook Download: PDF
2017
448 Seiten
Princeton University Press (Verlag)
978-1-4008-8818-4 (ISBN)

Lese- und Medienproben

Bit by Bit -  Matthew J. Salganik
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An innovative and accessible guide to doing social research in the digital ageIn just the past several years, we have witnessed the birth and rapid spread of social media, mobile phones, and numerous other digital marvels. In addition to changing how we live, these tools enable us to collect and process data about human behavior on a scale never before imaginable, offering entirely new approaches to core questions about social behavior. Bit by Bit is the key to unlocking these powerful methods-a landmark book that will fundamentally change how the next generation of social scientists and data scientists explores the world around us.Bit by Bit is the essential guide to mastering the key principles of doing social research in this fast-evolving digital age. In this comprehensive yet accessible book, Matthew Salganik explains how the digital revolution is transforming how social scientists observe behavior, ask questions, run experiments, and engage in mass collaborations. He provides a wealth of real-world examples throughout and also lays out a principles-based approach to handling ethical challenges.Bit by Bit is an invaluable resource for social scientists who want to harness the research potential of big data and a must-read for data scientists interested in applying the lessons of social science to tomorrow's technologies.Illustrates important ideas with examples of outstanding researchCombines ideas from social science and data science in an accessible style and without jargonGoes beyond the analysis of "e;found"e; data to discuss the collection of "e;designed"e; data such as surveys, experiments, and mass collaborationFeatures an entire chapter on ethicsIncludes extensive suggestions for further reading and activities for the classroom or self-study

Matthew J. Salganik is professor of sociology at Princeton University, where he is also affiliated with the Center for Information Technology Policy and the Center for Statistics and Machine Learning. His research has been funded by Microsoft, Facebook, and Google, and has been featured on NPR and in such publications as the New Yorker, the New York Times, and the Wall Street Journal.

Zusatzinfo 21 halftones. 58 line illus. 28 tables. 2 maps.
Verlagsort Princeton
Sprache englisch
Themenwelt Mathematik / Informatik Informatik Theorie / Studium
Mathematik / Informatik Informatik Web / Internet
Sozialwissenschaften Kommunikation / Medien Medienwissenschaft
Sozialwissenschaften Soziologie Empirische Sozialforschung
Schlagworte Alice and Bob • Amazon Mechanical Turk • a modest proposal • anonymization of data • Arvind Narayanan • Audit study • Belmont Report • Beneficence (ethics) • biases • Big Data • Bioethics • Bitcoin • Blue-ribbon panel • Boomerang effect (psychology) • Business Ethics • Calculation • Common Rule • confounding • Cover Letter • Cross-validation (statistics) • cybersecurity • data collection • Data Science • difference-in-differences estimators • differential privacy • Early Adopter • Economics • Elections • emotional contagion experiment • Estimand • estimation • Ethical Issues • external validity • Extrapolation • Fat Head • feature engineering • Field Experiment • Foldit • Full disclosure (computer security) • Galaxy Zoo • Hawthorne effect • Ignorability • Informed Consent • institutional review board • institutional review boards • instrumental variable • internal validity • Internet • Internet advertising • Interviewer effect • Joshua Blumenstock • Judea Pearl • Kaggle • machine learning • machine learning model • Marcel Duchamp • margin of error • Mass Collaboration • mass collaborations • Mass surveillance • Measurement • Meta-analysis • Microsoft Research • Motherhood penalty • MTurk • Multiple Choice • natural experiment • New Math • No Free Lunch (organization) • non-experimental approaches • Nonprobability sampling • nonresponse problem • observational study • OKCupid • online panel • open call mass collaborations • Operationalization • overfitting • participant • Pasteur's quadrant • Peer Review • political consulting • Polymath Project • Post hoc analysis • post-stratification • Power Analysis • Predictive Modelling • privacy • Probability Sampling • Program evaluation • Public Interest • Qualitative research • questionnaire • Race • Randomization • Randomized Controlled Trial • Randomized experiment • Reinventing Discovery • Renaissance Technologies • reproducibility • Research assistant • research ethics • Respondent • result • Sampling • Sampling (Statistics) • Scientific Misconduct • Scientist • scurvy • Second Source • sensitive data • Snapchat • Social desirability bias • Social Science • Spamming • Statistical conclusion validity • statistical significance • Study heterogeneity • Telephone interview • Tuskegee Syphilis Study • Twitter • usage data • Utah Data Center • variable cost • variance reduction • Voting • Website • Working Group
ISBN-10 1-4008-8818-2 / 1400888182
ISBN-13 978-1-4008-8818-4 / 9781400888184
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