Social media and user engagement are bigger than ever. Users are presented with various types of content curated by algorithms, which partially dictate what is shown to them. These algorithms lack transparency and clarity for the user. In this thesis we have developed a toolset to tail fit data of user engagement to show what behaviours this data actually shows. We want to see the differences between categories of content and show how user engagement in social media behaves. From our study we have found that there are differences between how users engage with different leanings within political content andcontents of differing credibility. We have also found that more narrow metrics in choosingdata can present different results and behaviours. From this we can determine that choice of data is crucial when working with tails. Future work is imperative to keep creating understanding for these social media platforms and how users engage with different types of content. To keep up with the constantly changing environment of social media new tools and methods will needed to create understanding for our most used platforms for public interaction.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-205371 |
| Date | January 2024 |
| Creators | Bruno, ELias, Lidberg, Erik |
| Publisher | Linköpings universitet, Institutionen för datavetenskap |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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