Abstract
The emergence of generative artificial intelligence applications in recent years has opened up the possibility of automatically generating text tailored to the needs of users. However, is the text generated by these tools easily readable and understandable? This study aims to analyze the ChatGPT's capacity to generate easy to understand texts in Spanish, while adhering to the recommended guidelines for Plain Language. The comprehensiveness of several websites belonging to the Public Administration in Spain has been analyzed. Moreover, ChatGPT was requested to enhance these texts in accordance with the guidelines of Plain Language in Spanish. The original texts and those generated by ChatGPT were then compared to analyze the primary linguistic indicators of different Plain Language guidelines. The study presents a quantitative analysis demonstrating that the new texts generated by ChatGPT do not adhere to Plain Language guidelines. Additionally, the study highlights the use of linguistic elements that should be avoided.
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Acknowledgements
This research has been partially funded by INSIGHT research project (PID2022-137344OB-C32) and the grant for research contracts PEJ-2021-AI/SAL-21563. We also thank Santiago Moreno Fernandez, Victor Muñoz-Velasco and Changao Wu for their support in the PLN analyzer.
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Appendix I. Linguistic Elements Analyzed
Appendix I. Linguistic Elements Analyzed
Table 3 shows the comparative data in original text (O) and generated text (G) using ChatGPT system for the 10 texts extracted from the Spanish Government web pages. Boxed bold text is used to highlight when the generated text is worse than the recommendation.
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Sastre, A., Iglesias, A., Morato, J., Sanchez-Cuadrado, S. (2024). Is ChatGPT Able to Generate Texts that Are Easy to Understand and Read?. In: Rocha, Á., Adeli, H., Dzemyda, G., Moreira, F., Poniszewska-Marańda, A. (eds) Good Practices and New Perspectives in Information Systems and Technologies. WorldCIST 2024. Lecture Notes in Networks and Systems, vol 987. Springer, Cham. https://doi.org/10.1007/978-3-031-60221-4_14
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