Section outline

  • Course Overview

    This course will set you up to effectively plan, gather and analyze social media data, equipping you to undertake research projects using social media data.

    Learning Outcomes

    This course will help you to:

    1. Understand how social media data presents challenges that differ from other types of data, particularly in relation to research ethics.
    2. Be empowered to effectively plan a social media data based project, including the data collection strategy, data storage and curation, and analysis.
    3. Gather, clean and analyze social media data using Workbench.

    • Course Instructor: James Allen-Robertson

      • James Allen-Robertson

        James is a Computational Social Scientist in the Department of Sociology, University of Essex. His work focuses on utilizing data science tools, including large-scale text analysis, social network analysis and computer-vision as aids to explore social science problems. James is also the director of the BSc Sociology with Data Science at the University of Essex and author of Digital Culture Industry: A History of Digital Distribution (2013). James believes that technology needs more social science, and vice-versa.

        View Bio for James Allen-Robertson

      • Course Resources

        You will need to access certain files and resources throughout the course to get the most out of the activities. You can find them all here. 

      • Video Transcripts

        You can access all video transcripts here.

      • Pre-Course Self Assessment

        Before you dive into this course, spend a few moments reflecting on your familiarity with the topic and your current level of skills confidence. 

        You will then re-visit the same questions in our Post-Course Self Assessment and reflect on how the course has helped you develop in confidence and grow your skills. 

        • Collecting Social Media Data

          This course will help you to:

          1. Understand how social media data presents challenges that differ from other types of data, particularly in relation to research ethics.
          2. Be empowered to effectively plan a social media data based project, including the data collection strategy, data storage and curation, and analysis.
          3. Gather, clean and analyze social media data using Workbench.

        • Post-Course Self Assessment

          Now you’ve completed the course, spend a few moments reflecting on where your familiarity with the topics and your confidence skills levels are at now. 

          Has the course helped you develop new skills and grow your confidence?

          You'll need to complete the Post-Course Self Assessment in order to download your certificate. If you didn't do the Pre-Course Self Assessment before starting the course, please go to the top of the page and reflect on your familiarity with the topic and your level of skills confidence before you started the course.

          • Completion: Certificate

            Completing all modules (plus the pre and post-course assessments) will unlock the course certificate, which you can then download here. Your course certificate will only be made available once you have completed all these sections.

            If you have difficulty accessing your certificate, please contact the Sage support team at: onlinesupport@sagepub.co.uk. You can also check out this FAQ page which may be helpful.

            • Give Feedback About This Course

              Did you enjoy the course? Please take two minutes to share your feedback. We use learner feedback in future course updates and developments to provide an excellent learning experience.

            • Accessibility

              We have high standards of accessibility on Sage Campus and as of May/June 2024 all activities within this course are keyboard and screen reader compatible. For more details on accessibility standards, please see the Sage Campus Accessibility Guide.

              For those using assistive technology, please note that within this course:

              • Tab components: JAWS and NVDA behave slightly differently. For NVDA to keep reading, it is best to exit focus mode and go back to browse mode. 
              • Matching: JAWS does not read out question label on dropdown focus.