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Welcome 1st Computational Social Science Workshop 2013 at GESIS
Welcome 1st Computational Social Science Workshop 2013 at GESIS
Welcome 1st Computational Social Science Workshop 2013 at GESIS
Welcome 1st Computational Social Science Workshop 2013 at GESIS
Welcome 1st Computational Social Science Workshop 2013 at GESIS
Welcome 1st Computational Social Science Workshop 2013 at GESIS
Welcome 1st Computational Social Science Workshop 2013 at GESIS
Welcome 1st Computational Social Science Workshop 2013 at GESIS
Welcome 1st Computational Social Science Workshop 2013 at GESIS
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Welcome 1st Computational Social Science Workshop 2013 at GESIS

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  • Welcome – say some words about WHY we initiated this workshop and what will except you today.
  • Transcript

    • 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. 2
    • 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] 3
    • 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 5
    • 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 6
    • 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 7
    • 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 8
    • 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 9
    • 9. Program 17:00 XMAS market tour 10

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