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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 7, 2022.
Abstract: Negation and speculation detection are critical for Natural Language Processing (NLP) tasks, such as sentiment analysis, information retrieval, and machine translation. This paper presents the first Arabic corpus in the review domain annotated with negation and speculation. The Negation and Speculation Arabic Review (NSAR) corpus consists of 3K randomly selected review sentences from three well-known and benchmarked Arabic corpora. It contains reviews from different categories, including books, hotels, restaurants, and other products written in various Arabic dialects. The negation and speculation keywords have been annotated along with their linguistic scope based on the annotation guidelines reviewed by an expert linguist. The inter-annotator agreement between two independent annotators, Arabic native speakers, is measured using the Cohen’s Kappa coefficients with values of 95 and 80 for negation and speculation, respectively. Furthermore, 29% of this corpus includes at least one negation instance, while only 4% of this corpus contains speculative content. Therefore, the Arabic reviews focus more on negation structures rather than speculation. This corpus will be available for the Arabic research community to handle these critical phenomena.
Ahmed Mahany, Heba Khaled, Nouh Sabri Elmitwally, Naif Aljohani and Said Ghoniemy, “Annotated Corpus with Negation and Speculation in Arabic Review Domain: NSAR” International Journal of Advanced Computer Science and Applications(IJACSA), 13(7), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130706
@article{Mahany2022,
title = {Annotated Corpus with Negation and Speculation in Arabic Review Domain: NSAR},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130706},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130706},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {7},
author = {Ahmed Mahany and Heba Khaled and Nouh Sabri Elmitwally and Naif Aljohani and Said Ghoniemy}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.