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СОИБИ ТАБРЕЗӢ ВА МАЪНОҲОИ МАҶҲУЛИ ЯК ФЕЪЛИ МАЪМУЛ ... : SOIB TABREZI AND FORGOTTEN MEANINGS OF ONE FREQUENTLY USED VERB OF THE TAJIK LANGUAGE ...
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The Classification of Professional Vocabulary in the Languages ...
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Unravelling the Stability of Nightingale Song Over Time and Space Using Open, Citizen Science and Shared Data ...
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Delimitation of dialect regions, subgroups, areas and types in the Czech Republic
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Goláňová, Hana. - : Charles University, Faculty of Arts, Institute of the Czech National Corpus, 2022
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Variation in Spanish/s: Overview and New Perspectives
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In: World Languages and Literatures Faculty Publications and Presentations (2022)
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MULDASA: Multifactor Lexical Sentiment Analysis of Social-Media Content in Nonstandard Arabic Social Media
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In: Applied Sciences; Volume 12; Issue 8; Pages: 3806 (2022)
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Abstract:
The semantically complicated Arabic natural vocabulary, and the shortage of available techniques and skills to capture Arabic emotions from text hinder Arabic sentiment analysis (ASA). Evaluating Arabic idioms that do not follow a conventional linguistic framework, such as contemporary standard Arabic (MSA), complicates an incredibly difficult procedure. Here, we define a novel lexical sentiment analysis approach for studying Arabic language tweets (TTs) from specialized digital media platforms. Many elements comprising emoji, intensifiers, negations, and other nonstandard expressions such as supplications, proverbs, and interjections are incorporated into the MULDASA algorithm to enhance the precision of opinion classifications. Root words in multidialectal sentiment LX are associated with emotions found in the content under study via a simple stemming procedure. Furthermore, a feature–sentiment correlation procedure is incorporated into the proposed technique to exclude viewpoints expressed that seem to be irrelevant to the area of concern. As part of our research into Saudi Arabian employability, we compiled a large sample of TTs in 6 different Arabic dialects. This research shows that this sentiment categorization method is useful, and that using all of the characteristics listed earlier improves the ability to accurately classify people’s feelings. The classification accuracy of the proposed algorithm improved from 83.84% to 89.80%. Our approach also outperformed two existing research projects that employed a lexical approach for the sentiment analysis of Saudi dialects.
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Keyword:
Arabic NLP; Arabic social media; lexical; Saudi dialects; sentiment analysis; Twitter
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URL: https://doi.org/10.3390/app12083806
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Greek-Canadian Koiné: The Emergence of a Koiné among Greek-Canadian Immigrants
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In: Languages; Volume 7; Issue 2; Pages: 110 (2022)
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| 11 |
Hypercorrection as a Symptom of Language Change: Majorcan Catalan Standard Pronunciation
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In: Languages; Volume 7; Issue 1; Pages: 57 (2022)
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Investigation on the Relationship between Biodiversity and Linguistic Diversity in China and Its Formation Mechanism
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In: International Journal of Environmental Research and Public Health; Volume 19; Issue 9; Pages: 5538 (2022)
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| 13 |
An indefinite maze : on the distribution of partitives and bare nouns in the Northern Italian dialects
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Indefinite determiners in two northern Italian dialects : A quantitative approach
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| 15 |
Beginning Moroccan Arabic (Darija): An OER Multimedia Textbook
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Advanced Moroccan Arabic (Darija): An OER Multimedia Textbook
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| 17 |
On Early English Pronunciation, With Especial Reference to Shakspere and Chaucer
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| 18 |
Ko Te Reo i Te Rarawa pēhea rainī te tūāhua reo o ngā mātua tūpuna i Pukepoto
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| 19 |
La designazione dell’area cromatica del GRIGIO nei dialetti italiani
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