Effect of topic on the Arabic language used on social networks and mobile phone communications

Khedher, Mohammed Z.; Abandah, Gheith A.; Al-Anati, Waleed A.; Ababneh, Sami; Zghoul, Ahmad A.; Hattab, Mamoun S.

doi:10.1109/aeect.2015.7360593

Cited by 4 publications

(3 citation statements)

References 8 publications

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“…It was also observed that the significant changes in the vernacular dialects of CA represent a real challenge to the performance of IR systems. Although these vernacular dialects of Arabic were not written and for centuries had been used only for oral communication, they are now widely used in writing, especially with the development of communication technologies, the proliferation of social media platforms, and the increasing interaction between people (Bassiouney, 2009;Harrat, Meftouh, & Smaili, 2019;Khedher et al, 2015).…”

Section: Methodsmentioning

confidence: 99%

Lexical Ambiguity in Arabic Information Retrieval: The Case of Six Web-Based Search Engines

Omar¹,

Aldawsari²

2020

IJEL

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In recent years, both research and industry have shown an increasing interest in developing reliable information retrieval (IR) systems that can effectively address the growing demands of users worldwide. In spite of the relative success of IR systems in addressing the needs of users and even adapting to their environments, many problems remain unresolved. One main problem is lexical ambiguity which has negative impacts on the performance and reliability of IR systems. To date, lexical ambiguity has been one of the most frequently reported problems in the Arabic IR systems despite the development of different word sense disambiguation (WSD) techniques. This is largely attributed to the limitations of such techniques in addressing the issue of linguistic peculiarities. Hence, this study addresses these limitations by exploring the reasons for lexical ambiguity in IR applications in Arabic as one step towards reliable and practical solutions. For this purpose, the performances of six search engines Google, Bing, Baidu, Yahoo, Yandex, and Ask are evaluated. Results indicate that lexical ambiguities in Arabic IR applications are mainly due to the unique morphological and orthographic system of the Arabic language, in addition to its diglossia and the multiple colloquial dialects where sometimes mutual intelligibility is not achieved. For better disambiguation and IR performances in Arabic, this study proposes that clustering models based on supervised machine learning theory should be trained to address the morphological diversity of Arabic and its unique orthographic system. Search engines should also be adapted to the geographic location of the users in order to address the issue of vernacular dialects of Arabic. They should also be trained to automatically identify the different dialects. Finally, search engines should consider all varieties of Arabic and be able to interpret the queries regardless of the particular language adopted by the user.

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Section: Methodsmentioning

confidence: 99%

Lexical Ambiguity in Arabic Information Retrieval: The Case of Six Web-Based Search Engines

Omar¹,

Aldawsari²

2020

IJEL

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“…From a linguistic perspective, Khedher et al (2015) conducted a study that aimed to determine how the topic affects Arabic language in DMC such as Facebook, Twitter, news sites, and blogging sites and in mobile phone messaging. A comprehensive study was carried out in Jordan using 8,538 text samples from five different forums including WhatsApp and…”

Section: Cs In Saudi Arabiamentioning

confidence: 99%

The Social Aspects of Code-Switching in Online Interaction: The Case of Saudi Bilinguals

AlAbdulqader

2023

The European Conference on Language Learning 2023: Official Conference Proceedings

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This research aims to investigate the concept of code-switching (CS) between English and Arabic and the CS practices of Saudi online users via a Translanguaging (TL) lens for more inclusive view towards the nature of the data from the study. It employs Digitally Mediated Communication (DMC), specifically the WhatsApp and Twitter platforms to understand how the users employ online resources to communicate with others on a daily basis. This project looks beyond language and considers the multimodal affordances (visual and audio means) that interlocutors utilise in their online communicative practices to shape their online social existence.This exploratory study is based on a data-driven interpretivist epistemology as it aims to understand how meaning (reality) is created by individuals within different contexts. This project used a mixed-method approach, combining a qualitative and a quantitative approach.In the former, data were collected from online chats and interview responses, while in the latter a questionnaire was employed to understand the frequency and relations between the participants' linguistic, non-linguistic practices and their social behaviours. The participants were eight bilingual Saudi nationals (three men and five women, aged between 20 and 50 years old) who interacted with others online.The study data were gathered from 194 WhatsApp chats and 122 Tweets which were analysed and interpreted according to three levels: conversational turn-taking and CS; the linguistic description of the data; and CS and persona. This project contributes to the emerging field of analysing online Arabic data systematically, the field of multimodality and bilingual sociolinguistics. In addition, it bridges some of the existing gaps in the DMC literature. The findings of this study are that CS by its nature, and most of the findings, if not all, support Wei's (2018) notion of TL that multiliteracy is one's ability to decode multimodal communication, and that this multimodality contributes to the meaning.

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“…In an online survey administered in 8 Arab countries (Bahrain, Egypt, Jordan, Kuwait, Lebanon, Oman, Saudi Arabia and the UAE), Mouratada and Salem (2012:3) concluded that social media in the Arab world has significantly impacted societal and cultural change in the region. A study by Khedher et al (2015) showed that both standard Arabic, colloquial Arabic, and an English-Arabic mixed orthography (Arabizi) have been used by Arabic social media users. The results indicated that whereas standard Arabic is used in formal discourse, colloquial Arabic and Arabizi are targeted in casual conversation and informal communication.…”

Section: Review Of Related Literaturementioning

confidence: 99%

The Use of Arabic Neologisms in Social Media Applications

Hamdan¹

2021

IJAES

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This study examines the use of Arabic neologism in social media applications. It depicts the nature and size of this transformation, and the types of word formation processes which contributed to this phenomenon. The data for this research are collected from two sources: (1) major social media platforms, namely Facebook, Twitter, Instagram, WhatsApp, among others and (2) the responses of 100 university (under-graduate and post-graduate) students to a limited set of questions in which they are asked to (1) list the most commonly used Information and Communication Technology (ICT) and social media-motived terms, especially those which have been adapted to and integrated into the Arabic language morpho-phonemic and syntactic system (spoken and/or written), (2) show how often they use those terms especially when an Arabic equivalent/counterpart is available, and (3) give reasons for why they use them. The study shows that use of neologisms is attributed to reasons of practicality and convenience, accuracy and relevance, trendiness and internationalization, in addition to lack of equivalence in the Arabic language system. Further, the following processes which mark the integration of neologisms into the Arabic language system are identified: loan blends, syntactic changes, morpho-syntactic changes, phonemic changes, abbreviations and clipping.

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Effect of topic on the Arabic language used on social networks and mobile phone communications

Cited by 4 publications

References 8 publications

Lexical Ambiguity in Arabic Information Retrieval: The Case of Six Web-Based Search Engines

Lexical Ambiguity in Arabic Information Retrieval: The Case of Six Web-Based Search Engines

The Social Aspects of Code-Switching in Online Interaction: The Case of Saudi Bilinguals

The Use of Arabic Neologisms in Social Media Applications

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