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Arabic syntactic analyzer (ARSA): an automated tool for the analysis of Arabic written texts.

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Title: Arabic syntactic analyzer (ARSA): an automated tool for the analysis of Arabic written texts.
Authors: Alzahrani, Alaa1 (AUTHOR) alzahrani.alaaa@gmail.com, Alfaifi, Adel1 (AUTHOR) adalfaify@ksu.edu.sa
Source: Reading & Writing. Jan2026, Vol. 39 Issue 1, p365-395. 31p.
Subject Terms: *Fluency (Language learning), Linguistic analysis, Linguistic complexity, Arabic language, Digital technology, Hypothesis
Abstract: Research on the linguistic features of Arabic texts is scarce due to the limited resources available for the Arabic language. To address this issue, the present study introduces the Arabic syntactic analyzer (ARSA), a freely available command-line interface tool that is easy to use and involves nine syntactic complexity indices and four syntactic fluency indices. The validity of ARSA was tested by investigating the extent to which each of its indices could predict expert judgments of essay quality. Linear regression models revealed that five ARSA indices positively predicted expert ratings of Arabic essays. The stepwise multiple regression model indicated that three of the ARSA indices explained 23.0% of the total variance in writing quality. These results indicate that ARSA has some predictive validity in accounting for Arabic writing quality. Comparing our results to prior English research, we also observed some cross-linguistic variation in the relationship between syntactic complexity and writing quality. The introduction of ARSA has the potential to increase research on Arabic writing and broaden the scope of writing research. [ABSTRACT FROM AUTHOR]
Copyright of Reading & Writing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: <searchLink fieldCode="AR" term="%22Alzahrani%2C+Alaa%22">Alzahrani, Alaa</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> alzahrani.alaaa@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Alfaifi%2C+Adel%22">Alfaifi, Adel</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> adalfaify@ksu.edu.sa</i>
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  Data: *<searchLink fieldCode="DE" term="%22Fluency+%28Language+learning%29%22">Fluency (Language learning)</searchLink><br /><searchLink fieldCode="DE" term="%22Linguistic+analysis%22">Linguistic analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Linguistic+complexity%22">Linguistic complexity</searchLink><br /><searchLink fieldCode="DE" term="%22Arabic+language%22">Arabic language</searchLink><br /><searchLink fieldCode="DE" term="%22Digital+technology%22">Digital technology</searchLink><br /><searchLink fieldCode="DE" term="%22Hypothesis%22">Hypothesis</searchLink>
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  Data: Research on the linguistic features of Arabic texts is scarce due to the limited resources available for the Arabic language. To address this issue, the present study introduces the Arabic syntactic analyzer (ARSA), a freely available command-line interface tool that is easy to use and involves nine syntactic complexity indices and four syntactic fluency indices. The validity of ARSA was tested by investigating the extent to which each of its indices could predict expert judgments of essay quality. Linear regression models revealed that five ARSA indices positively predicted expert ratings of Arabic essays. The stepwise multiple regression model indicated that three of the ARSA indices explained 23.0% of the total variance in writing quality. These results indicate that ARSA has some predictive validity in accounting for Arabic writing quality. Comparing our results to prior English research, we also observed some cross-linguistic variation in the relationship between syntactic complexity and writing quality. The introduction of ARSA has the potential to increase research on Arabic writing and broaden the scope of writing research. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Reading & Writing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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