Data collection methods
Data collection on social media and digital platforms comes with a range of specificities and nuances that, unfortunately, differ across each platform. To facilitate research and give you an idea of what’s possible on which platform, this section outlines data collection approaches and introduces examples for TikTok, X (Twitter), and blogs (including code). Additional examples or contributions to data collections methods are welcome, suggestions are listed under (4) call for contributions.
Social media data types: An overview: If you are wondering what kinds of data you can access and anylse on social media, this chapter will provide orientation and clarity around terminology.
Common data collection methods: Focusing on TikTok as a case study, this chapter offers insights into the myriad ways one can audit an online platform. It underscores the importance of aligning the chosen method with the research question at hand. Drawing on our experiences with auditing recommender systems, this chapter presents a holistic understanding of TikTok’s practices.
Platform-specific guidelines, e.g. X API, Streaming data: X (Twitter) with its vast user base and real-time data, has always been a fertile ground for researchers and developers alike. This chapter provides a comprehensive guide to making the most out of the API, with specific attention to a newly developed Python library, underscoring its flexibility and scalability.
Webscraping techniques with R: In a constantly changing digital environment, adaptability is key. As various social networks have begun to limit access to their APIs—either monetising them or closing them altogether — researchers face the challenge of capturing crucial data. The significance of webscraping has thus resurged, offering an alternative means of data collection.
Contributions are welcome, particularly case studies on Facebook, Instagram, YouTube and other platforms as well as additional data collection tactics and methods.