Topic outline

  • Course Overview

    Utilizing big data is becoming increasingly important in social research, but it brings an array of ethical challenges and research design elements to consider. On this course, you’ll gain an understanding of the emerging field of social data science and take your first steps into the big data-driven approach to research, learning from recent examples of social data science publications and projects.

    Learning Outcomes

    This course will help you to:

    1. Understand the relationship between empirical research, theory generation and testing
    2. Define and formulate research problems, questions and hypotheses to be tested
    3. Understand the rationale for using qualitative or quantitative research methods and the integrated or complementary nature between different methods in mixed methods research designs
    4. Understand different forms of sampling, sampling error, and case selection, and their potential implications when interpreting findings
    5. Apply concepts of generalisability, validity, reliability, and replicability
    6. Understand ethical aspects of social data science and how to cope with them

  • Course Author

    • Dr Taha Yasseri


      Dr Taha Yasseri is a Senior Research Fellow in Computational Social Science at the Oxford Internet Institute, University of Oxford, an Alan Turing Fellow at the Alan Turing Institute for Data Science, and a Research Fellow in Humanities and Social Sciences at Wolfson College, University of Oxford.

      Dr Yasseri graduated from the Department of Physics at the Sharif University of Technology, Tehran, Iran, in 2005, where he also obtained his MSc in 2006, working on localization in scale free complex networks. In 2007, he moved to the Institute of Theoretical Physics at the University of Göttingen, Germany, where he completed his PhD in Complex Systems Physics in 2010. Prior to coming to Oxford, he spent two years as a Postdoctoral Researcher at the Budapest University of Technology and Economics.

      View Bio
    • Module One: What Is Social Data Science?

      Important note: Your progress on modules in this course will temporarily not be reflected in the progress tracking bars on this page, until we’ve deployed scheduled updates to the platform. In the meantime, please do not worry that 0% progress is shown on this page, your progress is still being saved and you can view your progress on your personalized dashboard on the SAGE Campus homepage. You also are still able to download the certificate upon completion. Apologies for any inconvenience caused.

      This module will help you to:

      1. Get introduced to social data science and be familiarized with both social data science and scientific methods
    • Module Two: How to Determine the Design Elements and Data Sources of a Research Project

      Important note: Your progress on modules in this course will temporarily not be reflected in the progress tracking bars on this page, until we’ve deployed scheduled updates to the platform. In the meantime, please do not worry that 0% progress is shown on this page, your progress is still being saved and you can view your progress on your personalized dashboard on the SAGE Campus homepage. You also are still able to download the certificate upon completion. Apologies for any inconvenience caused.

      This module will help you to:

      1. Learn how to determine the main parameters of a research project including boundaries, scale and time resolution of your research, what big data is, how it differs to traditional data collection and what consent refers to
    • Module Three: What Methods Can We Use in Social Data Science?

      Important note: Your progress on modules in this course will temporarily not be reflected in the progress tracking bars on this page, until we’ve deployed scheduled updates to the platform. In the meantime, please do not worry that 0% progress is shown on this page, your progress is still being saved and you can view your progress on your personalized dashboard on the SAGE Campus homepage. You also are still able to download the certificate upon completion. Apologies for any inconvenience caused.

      This module will help you to:

      1. Become familiarized with the toolset of social data science, covering both quantitative, qualitative and mixed methods
    • Module Four: What Can be Learned From Your Research?

      Important note: Your progress on modules in this course will temporarily not be reflected in the progress tracking bars on this page, until we’ve deployed scheduled updates to the platform. In the meantime, please do not worry that 0% progress is shown on this page, your progress is still being saved and you can view your progress on your personalized dashboard on the SAGE Campus homepage. You also are still able to download the certificate upon completion. Apologies for any inconvenience caused.

      This module will help you to:

      1. Learn to develop research questions and hypotheses, be familiarized with validity, reproducibility, replicability and generalizability
    • Module Five: What Is Ethical Social Data Science?

      Important note: Your progress on modules in this course will temporarily not be reflected in the progress tracking bars on this page, until we’ve deployed scheduled updates to the platform. In the meantime, please do not worry that 0% progress is shown on this page, your progress is still being saved and you can view your progress on your personalized dashboard on the SAGE Campus homepage. You also are still able to download the certificate upon completion. Apologies for any inconvenience caused.

      This module will help you to:

      1. Get familiarized with the main ethical challenges in social data science and how to cope with them