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ПРЕЦЕДЕНТНЫЕ ФЕНОМЕНЫ В ПАРЕМИОЛОГИЧЕСКОМ ПРОСТРАНСТВЕ АВАРСКОГО И АРАБСКОГО ЯЗЫКОВ ... : PRECEDENT PHENOMENA IN THE PAREMIOLOGICAL SPACE OF THE AVAR AND ARABIC LANGUAGES ...
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Cross-Lingual Transfer Learning for Arabic Task-Oriented Dialogue Systems Using Multilingual Transformer Model mT5
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In: Mathematics; Volume 10; Issue 5; Pages: 746 (2022)
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A Survey of Al-Jumal Al-Ashartiyyah (The Conditional Sentences) in Arabic Language ...
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A Survey of Al-Jumal Al-Ashartiyyah (The Conditional Sentences) in Arabic Language ...
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Female rap in Arab countries. The case of Mayam Mahmoud ; Rap femenino en países árabes. El caso de Mayam Mahmoud
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Variation et représentation linguistique dans la variété arabe d'Ouezzane: lorsque le quantitative n'explique pas tout
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СОМАТИЧЕСКИЕ ФРАЗЕОЛОГИЧЕСКИЕ ЕДИНИЦЫ ДАРГИНСКОГО И АРАБСКОГО ЯЗЫКОВ С ЗООМОРФНЫМ КОДОМ КУЛЬТУРЫ ... : SOMATIC PHRASEOLOGICAL UNITS OF DARGIN AND ARABIC LANGUAGES WITH ZOOMORPHIC CULTURE CODE ...
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А.А. Омаров. - : Мир науки, культуры, образования, 2021
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РЕАЛИЗАЦИЯ ПРИНЦИПОВ ЭКОНОМИИ РЕЧЕВЫХ УСИЛИЙ НОСИТЕЛЯМИ ВОЕННЫХ СОЦИОЛЕКТОВ ... : IMPLEMENTATION OF THE PRINCIPLES OF SPEECH EFFORTS ECONOMY BY DIFFERENT MILITARY SOCIAL DIALECT SPEAKERS ...
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Дёмин, П.Е.; Харламов, А.А.. - : Автономная некоммерческая организация высшего образования «Российский новый университет», 2021
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The marginalization of the feminine in the grammatical heritage of the Arabic language ...
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Πολυγλωσσία και γλωσσομάθεια στα Βαλκάνια (β΄ μισό 15ου-μέσα 19ου αιώνα) ... : Multilingualism and λanguage-λearning in the Balkans (second half of 15th –middle of 19th centuries) ...
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Cognitively Driven Arabic Text Readability Assessment Using Eye-Tracking
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In: Applied Sciences ; Volume 11 ; Issue 18 (2021)
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The marginalization of the feminine in the grammatical heritage of the Arabic language
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Exploring tutoring and learning gains for learners of Arabic
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Amer, Mahmoud. - : University of Hawaii National Foreign Language Resource Center, 2021. : (co-sponsored by American Association of University of Supervisors and Coordinators; Center for Advanced Research on Language Acquisition; Center for Educational Reources in Culture, Language, and Literacy; Center for Open Educational Resources and Language Learning; Open Language Resource Center; Second Language Teaching and Resource Center), 2021
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The production and perception of peripheral geminate/singleton coronal stop contrasts in Arabic
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The impact of Arabic part of speech tagging on sentiment analysis: A new corpus and deep learning approach
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In: Test Series for Scopus Harvesting 2021 (2021)
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Abstract:
Sentiment Analysis is achieved by using Natural Language Processing (NLP) techniques and finds wide applications in analyzing social media content to determine people's opinions, attitudes, and emotions toward entities, individuals, issues, events, or topics. The accuracy of sentiment analysis depends on automatic Part-of-Speech (PoS) tagging which is required to label words according to grammatical categories. The challenge of analyzing the Arabic language has found considerable research interest, but now the challenge is amplified with the addition of social media dialects. While numerous morphological analyzers and PoS taggers were proposed for Modern Standard Arabic (MSA), we are now witnessing an increased interest in applying those techniques to the Arabic dialect that is prominent in social media. Indeed, social media texts (e.g. posts, comments, and replies) differ significantly from MSA texts in terms of vocabulary and grammatical structure. Such differences call for reviewing the PoS tagging methods to adapt social media texts. Furthermore, the lack of sufficiently large and diverse social media text corpora constitutes one of the reasons that automatic PoS tagging of social media content has been rarely studied. In this paper, we address those limitations by proposing a novel Arabic social media text corpus that is enriched with complete PoS information, including tags, lemmas, and synonyms. The proposed corpus constitutes the largest manually annotated Arabic corpus to date, with more than 5 million tokens, 238,600 MSA texts, and words from Arabic social media dialect, collected from 65,000 online users' accounts. Furthermore, our proposed corpus was used to train a custom Long Short-Term Memory deep learning model and showed excellent performance in terms of sentiment classification accuracy and F1-score. The obtained results demonstrate that the use of a diverse corpus that is enriched with PoS information significantly enhances the performance of social media analysis techniques and opens the door for advanced features such as opinion mining and emotion intelligence.
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Keyword:
Arabic language; Dialect Arabic; Neural network; Part of speech tagging; Sentiment analysis
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URL: https://ro.uow.edu.au/test2021/2030
https://doi.org/10.1016/j.procs.2021.03.026
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Saudi Mothers' Experiences Maintaining Their Young Children's Arabic Language and Islamic-Saudi Identity
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Parametric synthesis of Arabic speech ; Synthèse paramétrique de la parole Arabe
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In: https://hal.univ-lorraine.fr/tel-03050597 ; Traitement du signal et de l'image [eess.SP]. Université de Lorraine; Université de Tunis El Manar (Tunisie), 2020. Français. ⟨NNT : 2020LORR0116⟩ (2020)
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