This thesis shall utilise digital humanities methods via modest data-collection tools to quantify and study the online discussion involving Russia and Ukraine online. The research shall apply sentiment analysis to Twitter data to understand the general divisiveness online relating to the war in Ukraine. In doing so, a foundation is formed to begin extrapolating theories on the extent to which disinformation and synthetic media shall mutate this already sensitive situation. Secondly, this thesis shall parse data from groups on the Russian website VK using groups which circulate blatantly dishonest content and disinformation, ultimately revealing how engagement and posting trends on these communities have developed over the timeline of this conflict. The research will also draw from two external studies to contrast the findings. Finally, beyond discussing past and present examples of disinformation, this thesis shall conclude by theorising the trajectory AI will take to alter this evolving dynamic. This troublesome theory is conceivable through mediums like deepfakes and predominantly concerns their scalability, which could shortly become mass-produced items as their creation becomes increasingly more accessible. This shall be attempted by quantifying the total number of tweets produced globally during the period the deepfake of president Zelensky circulated. Despite being in its infancy, this thesis shall ultimately argue that artificial media shall become more ubiquitous as catalysts of disinformation.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:lnu-117976 |
| Date | January 2022 |
| Creators | Logan, Toby |
| Publisher | Linnéuniversitetet, Institutionen för kulturvetenskaper (KV) |
| 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 |
| Relation | Linnaeus University Dissertations |
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