Talk given for Women in Data Science event in Zurich on 5th April 2019 about using crowdsourced data and interpreting the biases within

1. The role of innovative data collection
methods in advancing understanding, and
the importance of considering the biases
within.
Dr Reka Solymosi
@r_solymosi
Reka.Solymosi@Manchester.ac.uk

2. Lecturer in quantitative methods
Centre for Criminology
University of Manchester
“New” forms
of data
@r_solymosi

3. • Recall
• Interviewer bias
• Spatial resolution
@r_solymosi

4. Harnessing
information and
skills from large
crowds into one
collaborative
project.
@r_solymosi

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12. What’s in a name?
@r_solymosi

13. Gender
Anon: 66.8%
Male: 24.4%
Female: 8.6%
@r_solymosi

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17. Neighbourhood(?) guardianship
@r_solymosi

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25. CAUTION!
@r_solymosi

26. Mode of production
• Involved/ interested citizens
• Pareto principle (++)
@r_solymosi

27. @r_solymosi

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29. Ethical consideration
• Privacy/ surveillance
• Data ownership
• Data linkage
• Implications of findings (service slanting)
@r_solymosi

30. Possible solutions?
Weighting?
Small area estimation?
Creative ways to make use of biases
@r_solymosi

31. Thank you!
Questions?
@r_solymosi
reka.solymosi@manchester.ac.uk