Providing stress of poetry on the syllable-, the foot-, and the phonological word- levels is one of the essential objectives of Metrical Phonology Theory. The subsumed number and types of syllables, feet, and meters are steady in poetry compared to other literary texts that is why its analysis demonstrates one of the most outstanding and debatable metrical issues. The roots of Metrical Phonology Theory are derived from prosody which studies poetic meters and versification. In Arabic, the starting point of metrical analysis is prosodic analysis which can be attributed to يديهارفلا in the second half of the eighth century (A.D.). This study aims at pinpointing the values of two metrical parameters in modern Arabic poetry. To

Providing stress of poetry on the syllable-, the foot-, and the phonological word- levels is one of the essential objectives of Metrical Phonology Theory. The subsumed number and types of syllables, feet, and meters are steady in poetry compared to other literary texts that is why its analysis demonstrates one of the most outstanding and debatable metrical issues. The roots of Metrical Phonology Theory are derived from prosody which studies poetic meters and versification. In Arabic, the starting point of metrical analysis is prosodic analysis which can be attributed to يديهارفلا in the second half of the eighth century (A.D.). This study aims at pinpointing the values of two metrical parameters in modern Arabic poetry. To

     Sentiment Analysis is a research field that studies human opinion, sentiment, evaluation, and emotions towards entities such as products, services, organizations, events, topics, and their attributes. It is also a task of natural language processing. However, sentiment analysis research has mainly been carried out for the English language. Although the Arabic language is one of the most used languages on the Internet, only a few studies have focused on Arabic language sentiment analysis.

     In this paper, a review of the most important research works in the field of Arabic text sentiment analysis using deep learning algorithms is presented. This review illustrates the main steps used in these studies, which include

AA wahid, journal mustansiriyah of sports science, 2023

 Most of the propositions, after the Arabic letter reached a position of integrity and proficiency, the calligrapher turned to the production of calligraphic formations in various aesthetic and expressive forms, investing the spiritual energies in what these calligraphic compositions show in artistic paintings. It carries a lot of meanings that are embodied in linear formations, and in order to reach these expressions and know the effective positions of space, this research is concerned with studying these technical treatments. The first chapter included the research problem, which included a question about the effectiveness of space in the linear painting, the importance of research and the temporal and spatial boundaries. As for the s

Lexicography, the art and craft of dictionary-making, is as old as writing. Since its very early stages several thousands of years ago, it has helped to serve basically the every-day needs of written communication among individuals in communities speaking different languages or different varieties of the same language. Two general approaches are distinguished in the craft of dictionary-making: the semasiological and the onomasiological. The former is represented by usually-alphabetical dictionaries as such, i.e. their being inventories of the lexicon, while the latter is manifested in thesauruses. English and Arabic have made use of both approaches in the preparation of their dictionaries, each having a distinct aim ahead. Wit

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

    The weak and strong forms are so called because it is not their lexical content that primary matter, but the role they have in the sentence. The problematic confusion, our students encounter, in recognizing and producing the correct pronunciation of weak and strong forms of the English function words is the main incentive behind conducting  this study. In order to gather the data, this paper used two types of tests: a recognition test and a production test. The general results reached  through the analysis of the students' answers seem to conform to the researcher's assumption: students face a critical problem in recognizing and producing correct pronunciation of the weak and strong forms of the English funct