In an attempt to create a fake news detection tool using a large language model (LLM), the emphasis is on validating the effectiveness of this approach and then making the tooling readily available. With the current model of gpt-4-turbo-preview and its assistant capabilities combined with simple prompts tailored to different objectives. While tools to detect fake news and simplify the process are not new, insight into how they work and why is not commonly available, most likely due to the monetization around the current services. By building an open-source platform that others can expand upon, giving insight into the prompts used, and enabling experimentation and a baseline to start at when developing further or taking inspiration from. The results when articles are not willfully written as fake but missing key data are obviously very hard to detect. However, common tabloid-style news, which are often shared to create an emotional response, shows more promising detection results.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:lnu-130418 |
| Date | January 2024 |
| Creators | Jurgell, Fredrik, Borgman, Theodor |
| Publisher | Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM) |
| 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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