Everyday we are flooded with news from all around the world and this information can be overwhelming. In our study we analyze the possibilities to implement GPT-3 models in the work of news summarization in swedish and automize this process. In this study we also regard the ethic point of view, meaning if we can trust these GPT-3 models and give them the responsibility to make news summarizations. We studied three different GPT-3 models: ChatGPT, Megatron and GPT-SW3. We used a quantitative survey method where the participants got to rate the news summarizations made by the GPT-3 models. The participants got to rate the news summarizations based on the criterias language, contents and structure. We then took the mean value of the ratings from the survey to see the results. The results showed that ChatGPT was significantly the best of all the three GPT-models on all three criterias, and Megatron and GPT-SW3 performed significantly worse. This shows that these models still need some development to get to the same levels as ChatGPT. Despite ChatGPT being the best performing GPT-3 model it still had its weak sides. We noticed this through one article that had alot of factors included which meant alot of information for the GPT-3 models to condense. Through this study we could confirm that GPT-3 models who are further in their development, like ChatGPT can be used in the work of news summarization but should be used with cautioun of what articles it gets to summarize. This means that GPT-3 models still require human supervision for articles with too much information to condense.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:umu-208761 |
| Date | January 2023 |
| Creators | Pålsmark, Josefhina, A. Viklund, Teodor |
| Publisher | Umeå universitet, Institutionen för informatik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | Swedish |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | Informatik Student Paper Bachelor (INFSPB) ; 2023.34 |
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