Bit By Bit: Social Research in the Digital Age
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  • 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

What to read next

  • An ink blot (section 1.1)

For a more detailed description of the project of Blumenstock and colleagues, see chapter 3 of this book.

  • Welcome to the digital age (section 1.2)

Gleick (2011) provides a historical overview of changes in humanity’s ability to collect, store, transmit, and process information.

For an introduction to the digital age that focuses on potential harms, such as privacy violations, see Abelson, Ledeen, and Lewis (2008) and Mayer-Schönberger (2009). For an introduction to the digital age that focuses on opportunities, see Mayer-Schönberger and Cukier (2013).

For more about firms mixing experimentation into routine practice, see Manzi (2012), and for more about firms tracking behavior in the physical world, see Levy and Baracas (2017).

Digital age systems can be both instruments and objects of study. For example, you might want to use social media to measure public opinion or you might want to understand the impact of social media on public opinion. In one case, the digital system serves as an instrument that helps you do new measurement. In the other case, the digital system is the object of study. For more on this distinction, see Sandvig and Hargittai (2015).

  • Research design (section 1.3)

For more on research design in the social sciences, see King, Keohane, and Verba (1994), Singleton and Straits (2009), and Khan and Fisher (2013).

Donoho (2015) describes data science as the activities of people learning from data, and it offers a history of data science, tracing the intellectual origins of the field to scholars such as Tukey, Cleveland, Chambers, and Breiman.

For a series of first-person reports about conducting social research in the digital age, see Hargittai and Sandvig (2015).

  • Themes of this book (section 1.4)

For more about mixing readymade and custommade data, see Groves (2011).

For more about failure of “anonymization,” see chapter 6 of this book. The same general technique that Blumenstock and colleagues used to infer people’s wealth can also be used to infer potentially sensitive personal attributes, including sexual orientation, ethnicity, religious and political views, and use of addictive substances (Kosinski, Stillwell, and Graepel 2013).

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