A Comparison of the Results from Artificial Intelligence-based and Human-based Transport-related Thematic Analysis
Artificial intelligence (AI) tools (in particular Large Language Models) have the potential to reduce the time needed to perform thematic analysis. To better understand their potential in the transportation field, we compare human-based to AI-based outcomes. Our findings indicate that AI tools, such...
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| Format: | Article |
| Language: | English |
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Findings Press
2024-03-01
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| Series: | Findings |
| Online Access: | https://doi.org/10.32866/001c.94401 |
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| author | Thiago Carvalho Hisham Negm Ahmed El-Geneidy |
| author_facet | Thiago Carvalho Hisham Negm Ahmed El-Geneidy |
| author_sort | Thiago Carvalho |
| collection | DOAJ |
| description | Artificial intelligence (AI) tools (in particular Large Language Models) have the potential to reduce the time needed to perform thematic analysis. To better understand their potential in the transportation field, we compare human-based to AI-based outcomes. Our findings indicate that AI tools, such as ChatGPT, could synthetize and summarize major topics present in our dataset regardless of previous user exposure to the subject or not. Nonetheless, caution is required as results might miss the nuance of less frequent themes. These tools could be used to accelerate the process under the supervision of researchers and practitioners given responder consent and the following of ethical practices. |
| format | Article |
| id | doaj-art-82802e55b7ba40d08e708aa9d87284dd |
| institution | DOAJ |
| issn | 2652-8800 |
| language | English |
| publishDate | 2024-03-01 |
| publisher | Findings Press |
| record_format | Article |
| series | Findings |
| spelling | doaj-art-82802e55b7ba40d08e708aa9d87284dd2025-08-20T02:39:26ZengFindings PressFindings2652-88002024-03-0110.32866/001c.94401A Comparison of the Results from Artificial Intelligence-based and Human-based Transport-related Thematic AnalysisThiago CarvalhoHisham NegmAhmed El-GeneidyArtificial intelligence (AI) tools (in particular Large Language Models) have the potential to reduce the time needed to perform thematic analysis. To better understand their potential in the transportation field, we compare human-based to AI-based outcomes. Our findings indicate that AI tools, such as ChatGPT, could synthetize and summarize major topics present in our dataset regardless of previous user exposure to the subject or not. Nonetheless, caution is required as results might miss the nuance of less frequent themes. These tools could be used to accelerate the process under the supervision of researchers and practitioners given responder consent and the following of ethical practices.https://doi.org/10.32866/001c.94401 |
| spellingShingle | Thiago Carvalho Hisham Negm Ahmed El-Geneidy A Comparison of the Results from Artificial Intelligence-based and Human-based Transport-related Thematic Analysis Findings |
| title | A Comparison of the Results from Artificial Intelligence-based and Human-based Transport-related Thematic Analysis |
| title_full | A Comparison of the Results from Artificial Intelligence-based and Human-based Transport-related Thematic Analysis |
| title_fullStr | A Comparison of the Results from Artificial Intelligence-based and Human-based Transport-related Thematic Analysis |
| title_full_unstemmed | A Comparison of the Results from Artificial Intelligence-based and Human-based Transport-related Thematic Analysis |
| title_short | A Comparison of the Results from Artificial Intelligence-based and Human-based Transport-related Thematic Analysis |
| title_sort | comparison of the results from artificial intelligence based and human based transport related thematic analysis |
| url | https://doi.org/10.32866/001c.94401 |
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