Streamlining the Selection Phase of Systematic Literature Reviews (SLRs) Using AI-Enabled GPT-4 Assistant API
| Autor: | Jafari, Seyed Mohammad Ali |
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| Rok vydání: | 2024 |
| Předmět: | |
| Druh dokumentu: | Working Paper |
| Popis: | The escalating volume of academic literature presents a formidable challenge in staying updated with the newest research developments. Addressing this, this study introduces a pioneering AI-based tool, configured specifically to streamline the efficiency of the article selection phase in Systematic Literature Reviews (SLRs). Utilizing the robust capabilities of OpenAI's GPT-4 Assistant API, the tool successfully homogenizes the article selection process across a broad array of academic disciplines. Implemented through a tripartite approach consisting of data preparation, AI-mediated article assessment, and structured result presentation, this tool significantly accelerates the time-consuming task of literature reviews. Importantly, this tool could be highly beneficial in fields such as management and economics, where the SLR process involves substantial human judgment. The adoption of a standard GPT model can substantially reduce potential biases and enhance the speed and precision of the SLR selection phase. This not only amplifies researcher productivity and accuracy but also denotes a considerable stride forward in the way academic research is conducted amidst the surging body of scholarly publications. Comment: 11 pages, 5 figures |
| Databáze: | arXiv |
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