Computational Social Science For the Semantic Web



Tutorial Overview

With the growing interest into analysing and understanding the Semantic Web from a social perspective, we are now facing a time where we need to branch out to other disciplines in order to derive real-world meaning from our findings. Whilst traditionally the use of social science methods, theories and practices have been performed as an additional step within the process of data experimentation and analysis, real value is achieved by working with these approaches at their epistemological and ontological roots.

In this tutorial we will cover the basics of computational social sciences from a computer science perspective, exploring theory to the application of methods and techniques across various analysis scenarios. We will cover the application of theory as a means to interrogate the start-to-end process of data collection to analysis, the use of statistical methods in the case of sampling and representativeness, and how to add real-world meaning to highly quantified processes.

The tutorial will run as a half day event, with a series of hands-on activities and talks in order to provide an interactive and engaging learning process. Alongside our teaching we encourage participants to bring along their own research and/or analysis in order to discuss how the methods and techniques can be applied and provide them more social and meaning

cial science methods, theories and practices have been performed as an additional step within the process of data experimentation and analysis, real value is achieved by working with these approaches at their epistemological and ontological roots.

In this tutorial we will cover the basics of computational social sciences from a computer science perspective, exploring theory to the application of methods and techniques across various analysis scenarios. We will cover the application of theory as a means to interrogate the start-to-end process of data collection to analysis, the use of statistical methods in the case of sampling and representativeness, and how to add real-world meaning to highly quantified processes.

The tutorial will run as a half day event, with a series of hands-on activities and talks in order to provide an interactive and engaging learning process. Alongside our teaching we encourage participants to bring along their own research and/or analysis in order to discuss how the methods and techniques can be applied and provide them more social and meaning


Tutorial Agenda

  • 09:00 – 09:15 – Registration and Welcome

    • Quick round-table introduction for all participants. 30 seconds pitch for why they are attending.


  • 09:15 – 10:00 – Why, How  and When - Computational Social Science 101

    • Introductory session on the thinking and integration of social science within the computational science

  • 10:00 – 11:20  -- Tutorial 2: (Dominic) -- Critical, Poststructural and Post-modern theories for Data Science.

    • What are some of the social theories behind qualitative research and why should we integrate them into our exploration of social data? How do we do this and what does this mean for data science as a whole?

  • 11:20 - 11:50 - Refreshment Break


  • 11:50 – 13:10 – Tutorial 3: (Markus) -- Individual and Collective Phenomena on the Web


  • 13:10 – 13:30 – Q&A + Bring your own research to analysis

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