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
1.4.1 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
You are reading the Open Review Edition of
Bit by Bit
.
Click here to read the 1st Edition.
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
×
×
Buy The Book
Princeton University Press
Amazon
Barnes and Noble
IndieBound