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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
1.4.1 Readymades and Custommades
1.4.2 Simplicity over complexity
1.4.3 Ethics everywhere
1.5 Outline of the book
2 Observing behavior
2.1 Introduction
2.2 Big data
2.3 Common characteristics of big data
2.3.1 Characteristics that are generally good for research
2.3.1.1 Big
2.3.1.2 Always-on
2.3.1.3 Non-reactive
2.3.2 Characteristics that are generally bad for research
2.3.2.1 Incomplete
2.3.2.2 Inaccessible
2.3.2.3 Non-representative
2.3.2.4 Drifting
2.3.2.5 Algorithmically confounded
2.3.2.6 Dirty
2.3.2.7 Sensitive
2.4 Research strategies
2.4.1 Counting things
2.4.1.1 Taxis in New York City
2.4.1.2 Friendship formation among students
2.4.1.3 Censorship of social media by the Chinese government
2.4.2 Forecasting and nowcasting
2.4.3 Approximating experiments
2.4.3.1 Natural experiments
2.4.3.2 Matching
2.5 Conclusion
Technical appendix
Further commentary
Activities
3 Asking questions
3.1 Introduction
3.2 Asking vs. 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
3.4.1 Probability sampling: data collection and data analysis
3.4.2 Non-probability samples: weighting
3.4.3 Non-probability samples: sample matching
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 other data
3.6.1 Amplified asking
3.6.2 Enriched asking
3.7 Conclusion
Technical appendix
Further commentary
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 Just do it yourself
4.5.1.1 Use existing environments
4.5.1.2 Build your own experiment
4.5.1.3 Build your own product
4.5.2 Partner with the powerful
4.6 Advice
4.6.1 Create zero variable cost data
4.6.2 Replace, Refine, and Reduce
4.7 Conclusion
Technical appendix
Further commentary
Activities
5 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
Further commentary
Activities
6 Ethics
6.1 Introduction
6.2 Three examples
6.2.1 Emotional Contagion
6.2.2 Taste, 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
Further commentary
Activities
7 The future
7.1 Looking foward
7.2 Themes of the 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
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2.3.2
Characteristics that are generally bad for research
2.3.2.1 Incomplete
2.3.2.2 Inaccessible
2.3.2.3 Non-representative
2.3.2.4 Drifting
2.3.2.5 Algorithmically confounded
2.3.2.6 Dirty
2.3.2.7 Sensitive
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