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jcois-1674
Linguistic deposits in the Arabic language
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Abstract of the research:

     This research sheds light on an important phenomenon in our Arabic language, which is linguistic sediments, and by which we mean a group of vocabulary that falls out of use and that native speakers no longer use it, and at the same time it happens that few individuals preserve the phenomenon and use it in their lives, and it is one of the most important phenomena that  It should be undertaken and studied by researchers;  Because it is at the heart of our huge linguistic heritage, as colloquial Arabic dialects retain a lot of linguistic sediments, and we usually find them at all levels of language: phonetic, banking, grammatical and semantic.  In the second requirement, I dealt with the nature of the terms linguistic sediments and linguistic stagnants. As for the third axis, I dealt with examples of linguistic sediments contained in the Arabic language.  It is not considered a departure from the rule, as some Arab scholars have said, but rather it is a stage of its development.

Key words:

- Terminology for subject of the study: rooting and etymology

- The nature of linguistic residues

- Examples of destroyed sediment in the Arabic language

 

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Publication Date
Thu Aug 10 2023
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This study aimed to examine the effects of electronic training to improve the skills of designing electronic courses for teachers of Arabic language in the colleges of education in Iraq. The descriptive approach is applied and the sample included 145 teachers of Arabic who were selected randomly from the colleges of education in Iraq. Moreover, the results reflected that e-training is effective in improving the skills related to designing online educational courses for teachers of Arabic in the colleges of education in Iraq. Besides, there was no difference between the mean of the respondents' responses to the total score of the tool on the role of electronic training to develop the skills related to electronic courses designing for teacher

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Wed Dec 11 2019
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Publication Date
Mon Jun 01 2020
Journal Name
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Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

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Wed Dec 11 2019
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Publication Date
Fri Dec 30 2022
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Sun Sep 30 2018
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