Toggle navigation
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
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
×
×
Buy The Book
Princeton University Press
Amazon
Barnes and Noble
IndieBound
