[2024]Digital Global Overview Report 2024 Meltwater.pdf
Welcome 1st Computational Social Science Workshop 2013 at GESIS
1. 1st Computational Social Science
(CSS) Workshop at GESIS
Claudia Wagner
GESIS – Leibniz Institut für die Sozialwissenschaften
2. Observations
Social Scientists are interested in
– how people
think/feel/behave in social
situations (social
psychology)
– relate to each other
(sociology)
– govern themselves (political
science)
– handle wealth (socioeconomics) and
– create culture
(anthropology)
The digital world is tracking the
social world more and more
closely.
This enables us to use
computation to discover patterns,
build models, validate social
theories and learn about societies.
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3. Computational Social Science
Computational Social Science:
“The science that investigates social phenomena through the
medium of computing and algorithmic data processing.”
CSSSA: http://computationalsocialscience.org/
[adapted from CSSSA]
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4. CSS Methods
• Empirical social science mainly focuses on reactive methods
• Disadvantages of reactive methods
– e.g., drop out rates, Hawthorne effect
• CSS has a focus on unobtrusive methods and found data
which are not new in social science
– e.g. study of floor tiles in the Chicago museum of science to explore
movement patterns and places of interest
• Disadvantages of unobtrusive methods and found data
– e.g. unobserved factors that impact the observations such as the
arrangement of furniture
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5. CSS
Opportunities and Challenges
• The ICT in general and the Web in specific can be seen
as a telescope that allows to observe the behavior of
individuals and groups of users over time
• ICT and the Web can also enable online laboratories
• Challenges
– Develop computational methods/approaches for tackling social
science questions
– Estimate and understand bias and limitations of found data
– Develop technologies for online laboratories
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6. Aims of the Workshop
• What research at WEST/GESIS contributes to
the CSS research field?
• Discover overlapping interests
• Discover collaboration possibilities
• Plan future collaborations
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7. Program
Network Session:
• 10.30 - 11:00 Predicting negative Links, Julia Perl
• 11:00 - 11:30 Doing politics in Twitter, Haiko Lietz
• 11:30 - 12:00 Method for generating networks with given
values of arbitrary graph measures, Jérôme Kunegis
• 12:00 - 12.15 The Relevance of Social Capital for Firms
involved in Open Source Software Development, Dirk
Homscheid
12:15 - 13.00 Lunch
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8. Program
Social Science Support and Applications Session:
• 13:00 - 13:20 The Hidden Data in Social Media Research - First Insights
from Expert Interviews, Katrin Weller und Katharina Kinder-Kurlanda
• 13:20 - 13:40 Exploring the challenge of linking scientific publications and
studies with crowd workers instead of domain experts, Cristina Sarasua
• 13:40 - 14:00 Spatio-temporal dietary patterns using Web Usage Data,
Claudia Wagner
• 14:00 - 14:30 Why Latent? Arnim Bleier
14.30-14.45 coffee & Working group formation
•
•
14:45 - 16:15 Open forum for discussions within working groups
16:15 - 16.45 Summary & Conclusions from Working Groups
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