Saudi Cultural Missions Theses & Dissertations
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Item Open Access Saudi Bilinguals’ Language Preferences for Emotional Expression: Exploring Their Language Emotional Resonance and Codeswitching Habits(Saudi Digital Library, 2023-12-01) Alghamdi, Shahad Abdulaziz Hassan; Dewaele, Jean-MarcThe present study follows the wave of research regarding language and emotions (Harris et al., 2003; Dewaele, 2004b, 2006, 2010; Panicacci & Dewaele, 2018; Dewaele et al., 2023) by investigating the relationship between Saudi bilinguals’ language emotional resonance (LER) and codeswitching (CS) habits on their language preferences for emotional expression. It examines the effects of sociobiographical factors (gender and education level), linguistic factors (frequency of use, proficiency levels, and language dominance) of their Arabic L1 and English L2, and topic (personal/emotional, taboo/swearwords, religious, and hobbies and interests) and interlocutor (family, friends, colleagues, and strangers) types on the mentioned dependent variables. 172 Saudi participants filled out an online questionnaire adapted from the BEQ (Dewaele & Pavlenko, 2001-2003) and the RER-LX scale (Toivo et al., 2022). The collected data went under quantitative descriptive analyses. The findings elucidated that females had higher LER for the second language (L2) and CS more frequently, and participants with lower degrees experienced more CS. Moreover, participants who were more proficient in the L2 and used it often still preferred the first language (L1) for emotional expression. Furthermore, topic and interlocutor types majorly affected CS frequency, and L1 had higher LER and is most participants' preferred language for emotional expression. Finally, the participants were shown to have reduced emotional resonance (RER) for the L2 and used it as a distancing mechanism. This study represents the dynamic nature between LER and CS for bilingual speakers. The implications of this dissertation suggest increasing the sample size, including age of acquisition (AoA) and context of acquisition (CoA) as preliminary variables, and employing proficiency assessments for better accuracy of results in future research.61 0Item Restricted English-Arabic Cross-Language Plagiarism Detection(2022) Alotaibi, Naif; Joy, MikeThe advancement of the information era and technology has contributed to the rapid growth of digital text libraries and automatic machine translation systems. The machine translation tools facilitate translating texts from one language into another. Those have resulted in increasing the content accessible in different languages, which makes it easy to perform translated plagiarism, which is referred to as “cross-language plagiarism”. Identification of plagiarism amongst texts in different languages is more challenging than recognizing plagiarism within a corpus written in the same language. This research proposes a new framework for enhancing English-Arabic cross-language plagiarism detection at the sentence level. The framework comprises of two phases: the first phase is feature extraction, while the second is plagiarism detection based on a supervised machine learning classification model. Phase one is concerned with extracted features among English-Arabic cross-language sentences, where we propose approaches to extracting sets of features at lexical, semantic and syntactic levels. This phase involves two components. The first relies on translation plus a monolingual, pretrained word embedding model, integrated with term frequency inverse document frequency (TFIDF), and part of speech (POS) scheme methods, as well as word order information. The second component employs a pre-trained multilingual model for determining semantic relatedness between cross-language sentence pairs. In terms of the second phase, we propose to apply and examine using various supervised machine learning classifier methods, along with the extracted features and with combinations of those features to assist in the task of classifying sentences as either plagiarized or non-plagiarized. Each phase was assessed using different datasets. The experimental results for phase one on different benchmark datasets, such as SemEval-2017, show the proposed methods for extracted features achieved improvement when compared against the baselines and other methods. Analysis of experimental data for phase two demonstrates that using extracted features and their combinations with various supervised machine learning classification methods achieves promising results. Ultimately, using the combination of extracted features along with a supervised ensemble machine learning classifier achieves the best classification results.36 0Item Restricted ARABIC AND ENGLISH CODE-SWITCHING IN INTERNET MEMES: A CONSTRUCTION OF A GLOBAL IDENTITY OR A CASE OF LINGUISTIC DOMINANCE(2023-05-10) Al-Rowais, Hawazen; Maxwell, JudithThis dissertation attempts to capture a thumbnail sketch of the ever-changing and evolving linguistic background in Saudi Arabia. Code-switching of Arabic and English in Internet Memes research is scarce; thus, this dissertation aims to explore this phenomenon by collecting a corpus of internet memes with English and Arabic code-switching. The objectives of this research are fourfold: First, it seeks to examine the types and functions of Arabic and English code-switching used in internet memes. Second, explore the social motivations behind code-switching in internet memes. Third, detect the features that elicit humor in internet memes using code-switching between Arabic and English. The fourth and final objective inspects the identities negotiated within internet memes through code- switching. As truncates of cultural units, Internet memes are loaded with references and hinge greatly on intertextuality. When you add an equally loaded linguistic phenomenon, such as code-switching, to that multimodal, multi-layered units, the complexity of internet memes is expanded. With this density of sub-texts and embedded cultural and social norms and values, an explorative approach is needed for collecting and analyzing internet memes with code-switching. The theoretical background I adapted for this dissertation is the interpretivism paradigm, first mentioned by Max Weber (Burger, 1977). Under this paradigm, subjective human experiences as data and analysis sources are just as imperative for generating generalizations as objective and quantitative data. I was able to look at personal experiences in Internet memes due to the social salience of Internet memes and the cultural and community values insights they provide. This view allows for an explorative approach to my data and the objectives of this dissertation. For data collection and to capture the background of internet memes collected, I follow MEMEography as an approach (Kaltenhauser et al., 2021), a digital ethnographic approach that focuses on the collection and analysis of Internet meme and their elements. Moreover, it allows for a manual technique in finding and choosing Internet memes centering around the topic of research rather than an automated and systematic collection approach. This digital ethnographic collection approach permitted looking at other aspects of social media platforms to collect more background information. As for data analysis, the thematic analysis approach (Braun & Clarke, 2006, 2012) was applied to the internet memes corpus. This dissertation assumes a qualitative data analysis, and thematic analysis provides the accessibility and flexibility to qualitative analysis. It allowed me to look at internet memes from a thematic standpoint, where the elements and the sub-texts residing within the memes are reviewed and read through to discern more extensive and all-embracing patterns. Key findings for the data analysis showed a negotiation of dual citizenship and identities, local Saudi versus global personas. The use of trending or referential English words while using local or Arabic-based meme templates indicates an appropriation of the global culture to the local one. Moreover, there was a clear social value assigned to English as a language, yet this prestige and social value competed with Standard Arabic. The memes with Standard Arabic code-switching assigned a higher value to Standard Arabic over English. However, English and Standard Arabic take precedence over Saudi Dialect. Furthermore, the memes on gender showed the utilization of global culture versus local culture, where ‘strong independent woman’ was reappropriated to fit the current social views on the matter within the Saudi community. This dissertation provided an explorative view of the linguistic setting in the cyber- Saudi speech community put forth in internet memes. Internet memes have become a part of our daily communication. Their condensed and brief forms provide a fertile field for research, especially when paired with language contact phenomena such as code-switching. This research calls for more attention to be given to the intricacy of both phenomena, i.e., internet memes and code-switching.54 0