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Abstract
This paper explores (im)politeness conceptualizations and evaluations and the moral foundations of lay notions of (im)politeness in Syrian Arabic. The data were collected using an online questionnaire which was administered to 88 native speaking participants. The results show that participants consider politeness and impoliteness as polar opposites; both are viewed as (in)consideration for others, chiefly conveyed through (dis)respect, and upholding/violating appropriate behaviors, respectively. Moreover, the results show that notions of hierarchical respect, face, equity rights, reciprocity, and attending to others' needs are central in motivating participants' views of (im)politeness. These notions are rooted in the moral foundations of authority/respect, fairness/reciprocity, and harm/care. Additionally, interesting findings emerge in that politeness in Syrian Arabic appears to be more of a relational phenomenon, based on morality, which is in line with contemporary views on politeness, than a rational and strategic behavior, as theorized in classical approaches.

The hypothesis the author starts from is that the so-called 'explanations' of sex-dialects found in the literature, can only be the consequences of the societal norms and economic positions of males and females in a given society. Thus taboo, invasion theory and 'gender display' are consequences which lead to linguistic differentiation and not the causes of such phenomena

One of the core dominant events, in the Middle East in 21th century, was Arab Spring revolutions in 2010-2011. These revolutions aimed to achieve democracy and get rid of the dictator regimes in the Arab countries. No doubt that Arab Spring had political social and economic reasonable and significant impacts. This paper will examine various reflections on the Arab revolutions of the Arab Spring (2010-2011) through modern Arab poetry, focusing on four selected poems as cases of study. In addition to the aimed historical reading, this paper attempts to analyse the selected poems focusing literary and poetic methods, as well as language and diction, comparing between them. For diversity, while all the selected poems are modern Arabic poetry, one of the selected poems is the neo-classic Arabic poetry of Ibrāhīm Obaydī, and the three others are free verse poetry from Ahmed Matar, Musʿab al-Mūrādī, and Ahmad Msāʿdih. Methodologically, this study is analytic, comparative and inductive, relying relevant poems of the selected four poets. This paper suggests not only that the Arab Spring played a significant historical role in the Middle East, leading to intensive civil and non-civil armed conflicts, but also, Modern Arab poetry contributes to historical documenting immortalizing the Arab Spring revolutions including their aims and motivations, as well as their social political and cultural impacts.

One of the core dominant events, in the Middle East in 21th century, was Arab Spring revolutions in 2010-2011. These revolutions aimed to achieve democracy and get rid of the dictator regimes in the Arab countries. No doubt that Arab Spring had political social and economic reasonable and significant impacts. This paper will examine various reflections on the Arab revolutions of the Arab Spring (2010-2011) through modern Arab poetry, focusing on four selected poems as cases of study. In addition to the aimed historical reading, this paper attempts to analyse the selected poems focusing literary and poetic methods, as well as language and diction, comparing between them. For diversity, while all the selected poems are modern Arabic poetry, one of the selected poems is the neo-classic Arabic poetry of Ibrāhīm Obaydī, and the three others are free verse poetry from Ahmed Matar, Musʿab al-Mūrādī, and Ahmad Msāʿdih. Methodologically, this study is analytic, comparative and inductive, relying relevant poems of the selected four poets. This paper suggests not only that the Arab Spring played a significant historical role in the Middle East, leading to intensive civil and non-civil armed conflicts, but also, Modern Arab poetry contributes to historical documenting immortalizing the Arab Spring revolutions including their aims and motivations, as well as their social political and cultural impacts.

The general adoption of "Arabic" numerals by European bookkeepers occurred at least five hundred years after their introduction to the scholarly world. The early availability yet late adoption of this numeration is shown to be due to several factors, not least to interplay between the culture and cultural conservatism of clerks and the educational and intellectual changes of the early Italian Renaissance.

"Arabic Glitch explores an alternative origin story of twenty-first century technological innovation in digital politics--one centered on the Middle East and the 2011 Arab uprisings. Developed from an archive of social media data collected over the decades following the 2003 U.S. invasion of Iraq, this book interrogates how the logic of programming technology influences and shapes social movements. Engaging revolutionary politics, Arab media, and digital practice in form, method, and content, Laila Shereen Sakr formulates a media theory that advances the concept of the glitch as a disruptive media affordance. She employs data analytics to analyze tweets, posts, and blogs to describe the political culture of social media, and performs the results under the guise of the Arabic-speaking cyborg VJ Um Amel. Playing with multiple voices that span across the virtual and the real, Sakr argues that there is no longer a divide between the virtual and embodied: both bodies and data are physically, socially, and energetically actual. Are we cyborgs or citizens--or both? This book teaches us how a region under transformation became a vanguard for new thinking about digital systems: the records they keep, the lives they impact, and how to create change from within"--

AbstractIn this article I present an analysis of split questions (SQs) in Modern Standard Arabic. I argue that this construction is best analyzed as a biclausal articulation, where two clauses are meditated by a special relation of coordination dubbed "Specifying Coordination." Contrary to the previous literature on SQs, I maintain, on empirical and conceptual grounds, that SQs are best derived in a movement‐free fashion by treating them as a constellation of two well‐motivated operations in the grammar: ellipsis and coordination. If on track, the merit of this proposal is to derive peripheral phenomena, such as SQs, from core principles of the grammar.

Abstract
As adaptation is often associated with localization, and with the promotion of transcreation as an extra service
in the industry, there is a need to analyze how and to what extent transcreation is used in localization as a type of
target-culture-focused translation. This paper looks into adaptation and analyzes transcreation as a translation strategy. It
investigates online promotional texts localized into Arabic (for Saudi Arabia) as an under-researched language in website
localization. The analysis follows a functionalist approach and examines 15 international corporate websites. The results
illustrate components of transcreated texts and shed light on the use of different procedures to achieve the creative persuasive
purpose.

The way from just read, to read & write web leads social networks users to be excited about distribution their feeling and opinions by several social media that support textual, audio and videos content. Few years ago, these opinions include various purposes such as: education, economic, political, and sport. With the increasing importance of these opinions, it becomes necessary to understand the meaning of them through the automatic analysis of user opinions. Opinion mining or sentiment analysis aims to fetch the attributes i.e. words from the opinions to decide the polarity of the users posts and comments in various topics depending on several linguistic techniques. The classical polarity classes consist of positive, negative and neutral. Since we have also unwanted comments such as advertising and misleading posts, some research studies added spam to the polarity classes. There are several studies focused on enhancing Arabic sentiment analysis but spam detection techniques are still limited. In this paper we used well-known Arabic sentiment analysis corpus and we automatically used term frequency– inverse document frequency (TFIDF) technique. We compared and evaluated three machine learning classifiers for detecting sentiment polarity using prediction evaluation measurements.

Twitter is one of the most popular online social networks for spreading propaganda and words in the Arab region. Spammers are now creating rogue accounts to distribute adult content through Arabic tweets that Arabic norms and cultures prohibit. Arab governments are facing a huge challenge in the detection of these accounts. Researchers have extensively studied English spam on online social networks, while to date, social network spam in other languages has been completely ignored. In our previous study, we estimated that rogue and spam content accounted for approximately three quarters of all content with Arabic trending hashtags in Saudi Arabia. This alarming rate, supported by autonomous concurrent estimates, highlights the urgent need to develop adaptive spam detection methods. In this work, we collected a pure data set from spam accounts producing Arabic tweets. We applied lightweight feature engineering based on rogue content and user profiles. The 47 generated features were analyzed, and the best features were selected. Our performance results show that the random forest classification algorithm with 16 features performs best, with accuracy rates greater than 90%.

Keywords provide the reader with a summary of the contents of the document and play a significant role in information retrieval systems, especially in search engine optimization and bibliographic databases. Furthermore keywords help to classify the document into the related topic. Keywords extraction included manual extracting depends on the content of the document or article and the judgment of its author. Manual extracting of keywords is costly, consumes effort and time, and error probability. In this research an automatic Arabic keywords extraction model based on deep learning algorithms is proposed. The model consists of three main steps: preprocessing, feature extraction and classification to classify the document tokens into keyword or not, Conventional Neural Networks (CNN) is used as a classifier.
Two types of dataset are building in this research to test the proposed model, the first dataset form Arab Journal for Scientific Publishing (AJSP), the other dataset from Jordan Journal of Social Sciences (JJSS). The experiment results indicate promising results in the field of Arabic keyword extraction; the average accuracy of Conventional Neural Networks is found 0.97 with average precision 0.92.