Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discriminate the polarity of sentiments. This paper proposes a hybrid method of linguistic and statistical features along with classification methods for Arabic sentiment analysis. Linguistic features contains stemming and POS tagging, while statistical contains the TF-IDF. A benchmark dataset of Arabic tweets have been used in the experiments. In addition, three classifiers have been utilized including SVM, KNN and ME. Results showed that SVM has outperformed the other classifiers by obtaining an f-score of 72.15%. This indicates the usefulness of using SVM with the proposed hybrid features.
This paper investigates the collocational use of irreversible food binomials in the lexicons of English (UK) and Arabic (Iraq), their word-order motivations, cultural background, and how they compare. Data consisted in sixteen pairs in English, versus fifteen in Arabic. Data analysis has shown their word order is largely motivated by logical sequencing of precedence; the semantically bigger or better item comes first and the phonologically longer word goes last. These apply in a cline of decreasing functionality: logical form first, semantic importance second, phonological form last. In competition, the member higher in this cline wins first membership. While the entries in each list clearly reflect culturally preferred food meals in the UK
... Show MoreA sentence is a key part of Spanish grammar and serves as the fundamental unit in constructing discourse. However, foreign language learners, particularly Arabic speakers, may face complex aspects that hinder their understanding and correct use of sentences. Additionally, there are at least two linguistic approaches that describe the use of compound sentences: one considers the sentence as the basic unit for discourse analysis, while other studies, starting with Van Dijk (2003), emphasize the importance of understanding both the partial and holistic structure of discourse. Therefore, we consider the significance of reviewing the linguistic differences between the native language and Spanish as a potential cause of misunderstanding a
... Show MoreNowadays, most of the on-chip plasmonic single-photon sources emit an unpolarized stream of single photons that demand a subsequent polarizer stage in a practical quantum cryptography system. In this paper, we numerically demonstrated the coupling of the light emitted from a quantum emitter (QE) at 700 nm wavelength to the propagation mode supported by an on-chip hybrid plasmonic waveguide (HPW) polarization rotator. Our results proved that the light emitted is linearly polarized at 0º, 45º/−45º, and 90º with propagation lengths of 5 μm, 3.3 μm, and 3.9 μm, respectively. Moreover, high power-conversion efficiency was obtained from an applied transverse magnetic (TM) mode (0º-polarization) to a transverse electric (TE) (90º-polari
... Show MoreThe letters are exposed in some texts of the classical Arabic language (poetry or prose), or in some of the Qur’anic texts, which are the main sources that were adopted on the day when provisions, rules and linguistic controls were established. I say that some of these letters are exposed in some contexts to deletion, mention, or change in the structure and shape of the letter. As for the omission, it is one of the aspects that distinguished Arabic, as well as other languages, for many purposes that differ among their user.
Gross domestic product (GDP) is an important measure of the size of the economy's production. Economists use this term to determine the extent of decline and growth in the economies of countries. It is also used to determine the order of countries and compare them to each other. The research aims at describing and analyzing the GDP during the period from 1980 to 2015 and for the public and private sectors and then forecasting GDP in subsequent years until 2025. To achieve this goal, two methods were used: linear and nonlinear regression. The second method in the time series analysis of the Box-Jenkins models and the using of statistical package (Minitab17), (GRETLW32)) to extract the results, and then comparing the two methods, T
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