Bit By Bit: Social Research in the Digital Age
  • About
    • Open Review
    • Citation
    • Code
    • About the Author
    • Privacy & Consent
  • Languages
    • English
    • Afrikaans
    • Albanian
    • Amharic
    • Arabic
    • Armenian
    • Azerbaijani
    • Basque
    • Belarusian
    • Bengali
    • Bosnian
    • Bulgarian
    • Catalan
    • Cebuano
    • Chichewa
    • Chinese Simplified
    • Chinese Traditional
    • Corsican
    • Croatian
    • Czech
    • Danish
    • Dutch
    • Esperanto
    • Estonian
    • Filipino
    • Finnish
    • French
    • Frisian
    • Galician
    • Georgian
    • German
    • Greek
    • Gujarati
    • Haitian Creole
    • Hausa
    • Hawaiian
    • Hebrew
    • Hindi
    • Hmong
    • Hungarian
    • Icelandic
    • Igbo
    • Indonesian
    • Irish
    • Italian
    • Japanese
    • Javanese
    • Kannada
    • Kazakh
    • Khmer
    • Korean
    • Kurdish (Kurmanji)
    • Kyrgyz
    • Lao
    • Latin
    • Latvian
    • Lithuanian
    • Luxembourgish
    • Macedonian
    • Malagasy
    • Malay
    • Malayalam
    • Maltese
    • Maori
    • Marathi
    • Mongolian
    • Myanmar (Burmese)
    • Nepali
    • Norwegian
    • Pashto
    • Persian
    • Polish
    • Portuguese
    • Punjabi
    • Romanian
    • Russian
    • Samoan
    • Scots Gaelic
    • Serbian
    • Sesotho
    • Shona
    • Sindhi
    • Sinhala
    • Slovak
    • Slovenian
    • Somali
    • Spanish
    • Sudanese
    • Swahili
    • Swedish
    • Tajik
    • Tamil
    • Telugu
    • Thai
    • Turkish
    • Ukrainian
    • Urdu
    • Uzbek
    • Vietnamese
    • Welsh
    • Xhosa
    • Yiddish
    • Yoruba
    • Zulu
  • Teaching
  • Media
  • Read Online
  • Buy the book
    • Princeton University Press
    • Amazon
    • Barnes and Noble
    • IndieBound
  • Preface
  • 1 Introduction
    • 1.1 An ink blot
    • 1.2 Welcome to the digital age
    • 1.3 Research design
    • 1.4 Themes of this book
    • 1.5 Outline of this book
    • What to read next
  • 2 Observing behavior
    • 2.1 Introduction
    • 2.2 Big data
    • 2.3 Ten common characteristics of big data
      • 2.3.1 Big
      • 2.3.2 Always-on
      • 2.3.3 Nonreactive
      • 2.3.4 Incomplete
      • 2.3.5 Inaccessible
      • 2.3.6 Nonrepresentative
      • 2.3.7 Drifting
      • 2.3.8 Algorithmically confounded
      • 2.3.9 Dirty
      • 2.3.10 Sensitive
    • 2.4 Research strategies
      • 2.4.1 Counting things
      • 2.4.2 Forecasting and nowcasting
      • 2.4.3 Approximating experiments
    • 2.5 Conclusion
    • Mathematical notes
    • What to read next
    • Activities
  • 3 Asking questions
    • 3.1 Introduction
    • 3.2 Asking versus observing
    • 3.3 The total survey error framework
      • 3.3.1 Representation
      • 3.3.2 Measurement
      • 3.3.3 Cost
    • 3.4 Who to ask
    • 3.5 New ways of asking questions
      • 3.5.1 Ecological momentary assessments
      • 3.5.2 Wiki surveys
      • 3.5.3 Gamification
    • 3.6 Surveys linked to big data sources
      • 3.6.1 Enriched asking
      • 3.6.2 Amplified asking
    • 3.7 Conclusion
    • Mathematical notes
    • What to read next
    • Activities
  • 4 Running experiments
    • 4.1 Introduction
    • 4.2 What are experiments?
    • 4.3 Two dimensions of experiments: lab-field and analog-digital
    • 4.4 Moving beyond simple experiments
      • 4.4.1 Validity
      • 4.4.2 Heterogeneity of treatment effects
      • 4.4.3 Mechanisms
    • 4.5 Making it happen
      • 4.5.1 Use existing environments
      • 4.5.2 Build your own experiment
      • 4.5.3 Build your own product
      • 4.5.4 Partner with the powerful
    • 4.6 Advice
      • 4.6.1 Create zero variable cost data
      • 4.6.2 Build ethics into your design: replace, refine, and reduce
    • 4.7 Conclusion
    • Mathematical notes
    • What to read next
    • Activities
  • 5 Creating mass collaboration
    • 5.1 Introduction
    • 5.2 Human computation
      • 5.2.1 Galaxy Zoo
      • 5.2.2 Crowd-coding of political manifestos
      • 5.2.3 Conclusion
    • 5.3 Open calls
      • 5.3.1 Netflix Prize
      • 5.3.2 Foldit
      • 5.3.3 Peer-to-Patent
      • 5.3.4 Conclusion
    • 5.4 Distributed data collection
      • 5.4.1 eBird
      • 5.4.2 PhotoCity
      • 5.4.3 Conclusion
    • 5.5 Designing your own
      • 5.5.1 Motivate participants
      • 5.5.2 Leverage heterogeneity
      • 5.5.3 Focus attention
      • 5.5.4 Enable surprise
      • 5.5.5 Be ethical
      • 5.5.6 Final design advice
    • 5.6 Conclusion
    • What to read next
    • Activities
  • 6 Ethics
    • 6.1 Introduction
    • 6.2 Three examples
      • 6.2.1 Emotional Contagion
      • 6.2.2 Tastes, Ties, and Time
      • 6.2.3 Encore
    • 6.3 Digital is different
    • 6.4 Four principles
      • 6.4.1 Respect for Persons
      • 6.4.2 Beneficence
      • 6.4.3 Justice
      • 6.4.4 Respect for Law and Public Interest
    • 6.5 Two ethical frameworks
    • 6.6 Areas of difficulty
      • 6.6.1 Informed consent
      • 6.6.2 Understanding and managing informational risk
      • 6.6.3 Privacy
      • 6.6.4 Making decisions in the face of uncertainty
    • 6.7 Practical tips
      • 6.7.1 The IRB is a floor, not a ceiling
      • 6.7.2 Put yourself in everyone else’s shoes
      • 6.7.3 Think of research ethics as continuous, not discrete
    • 6.8 Conclusion
    • Historical appendix
    • What to read next
    • Activities
  • 7 The future
    • 7.1 Looking forward
    • 7.2 Themes of the future
      • 7.2.1 The blending of readymades and custommades
      • 7.2.2 Participant-centered data collection
      • 7.2.3 Ethics in research design
    • 7.3 Back to the beginning
  • Acknowledgments
  • References

2 Observing behavior

  • 2.1 Introduction
  • 2.2 Big data
  • 2.3 Ten common characteristics of big data
    • 2.3.1 Big
    • 2.3.2 Always-on
    • 2.3.3 Nonreactive
    • 2.3.4 Incomplete
    • 2.3.5 Inaccessible
    • 2.3.6 Nonrepresentative
    • 2.3.7 Drifting
    • 2.3.8 Algorithmically confounded
    • 2.3.9 Dirty
    • 2.3.10 Sensitive
  • 2.4 Research strategies
    • 2.4.1 Counting things
    • 2.4.2 Forecasting and nowcasting
    • 2.4.3 Approximating experiments
  • 2.5 Conclusion
  • Mathematical notes
  • What to read next
  • Activities

Powered by Open Review Toolkit

Buy The Book

Image of Bit by Bit cover Princeton University Press Amazon Barnes and Noble IndieBound