Saudi Cultural Missions Theses & Dissertations
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Item Restricted Unveiling the Digital Divide: Public and Private Spaces on Social Media in the Saudi Context(La Trobe University, 2024-05) Bahabri, Alaa Sultan; Bahfen, Nasya; McCarthy, BrigidThe emergence of social media has significantly altered the traditional boundaries between public and private, creating blurred spaces. As users around the world navigate these novel spaces, considerable research shows that they utilise various strategies to manage public and private. In the Saudi context, previous studies have shown that Saudis – influenced by Islamic privacy norms– tend to strictly segregate public and private spaces on social media using several strategies. Nonetheless, much of this research has primarily focused on users, with little attention paid to the influence of digital elements. This study investigates a common strategy of navigating public and private in the Saudi context, which is the segregation of public and private spaces across platforms. The study takes into account the influence of the platform’s interface and affordances. The study was conducted through three phases of data collection and analysis. The first phase involved analysing social media platforms using a digital ethnography approach; the walkthrough methodology to demonstrate the platform’s interface and affordances of public and private space. The second phase focused on investigating users’ perspectives and behaviours related to public and private spaces across platforms using a questionnaire and interviews. Lastly, the third phase delved deeper into specific public and private spaces identified during the earlier phases through in-depth interviews and further analysis the online social norms of public and private space. This study argues that, as social media platforms blur the boundaries between public and private, the proliferation of social media has led Saudi users to heavily rely on segregating public and private spaces across these platforms, taking into account each platform's interface and affordances. This segregation reflects the Islamic notion of privacy, and it allowed users to reflect and facilitate their culture and social norms in the online space. The findings revealed that Saudis preferred platforms with default public or default private design, while they negotiate semi-public platforms. Twitter was favoured as a public space due to its default public interface design, while Snapchat’s was favoured as a private space. Conversely, Facebook’s semi-public nature was rejected due to perceived openness, leading to its designation as a niche network among Saudis. Instagram’s semi-public space was also negotiated and was used as a functional platform. Finally, TikTok was rejected due to the perception that it is not culturally appropriate. 5 Further analysis examined the social norms on Twitter and Snapchat, highlighting the differences in public and private interactions. The study found Twitter users exhibited cautious behaviour due to its public interface design, and presented a collective self, with either a serious or professional personas. In contrast, Snapchat provided a unique dynamic, particularly as older users were present on the platform, leading young users to create a more closed private space that differed from offline private circles. Overall, this research underscores the intricate interplay of culture, technology, and user behaviour in shaping Saudi Arabia’s digital landscape, emphasising the importance of considering both the cultural values and digital environments in understanding these dynamics for effective platform design and policymaking.15 0Item Restricted Automatic Detection and Verification System for Arabic Rumor News on Twitter(University of Technology Sydney, 2026-04) Karali, Sami; Chin-Teng, LinLanguage models have been extensively studied and applied in various fields in recent years. However, the majority of the language use models are designed for and perform significantly better in English compared to other languages, such as Arabic. The differences between English and Arabic in terms of grammar, writing, and word-forming structures pose significant challenges in applying English-based language models to Arabic content. Therefore, there is a critical need to develop and refine models and methodologies that can effectively process Arabic content. This research aims to address the gaps in Arabic language models by developing innovative machine learning (ML) and natural language processing (NLP) methodologies. We apply the developed model to Arabic rumor detection on Twitter to test its effectiveness. To achieve this, the research is divided into three fundamental phases: 1) Efficiently collecting and pre-processing a comprehensive dataset of Arabic news tweets; 2) The refinement of ML models through an enhanced Convolutional Neural Network (ECNN) equipped with N-gram feature maps for accurate rumor identification; 3) The augmentation of decision-making precision in rumor verification via sophisticated ensemble learning techniques. In the first phase, the research meticulously develops a methodology for the collection and pre-processing of Arabic news tweets, aiming to establish a dataset optimized for rumor detection analysis. Leveraging a blend of automated and manual processes, the research navigates the intricacies of the Arabic language, enhancing the dataset’s quality for ML applications. This foundational phase ensures removing irrelevant data and normalizing text, setting a precedent for accuracy in subsequent detection tasks. The second phase is to develop an Enhanced Convolutional Neural Network (ECNN) model, which incorporates N-gram feature maps for a deeper linguistic analysis of tweets. This innovative ECNN model, designed specifically for the Arabic language, marks a significant departure from traditional rumor detection models by harnessing the power of spatial feature extraction alongside the contextual insights provided by N-gram analysis. Empirical results underscore the ECNN model’s superior performance, demonstrating a marked improvement in detecting and classifying rumors with heightened accuracy and efficiency. The culmination of the study explores the efficacy of ensemble learning methods in enhancing the robustness and accuracy of rumor detection systems. By synergizing the ECNN model with Long Short-Term Memory (LSTM), Bidirectional LSTM (BiLSTM), and Gated Recurrent Unit (GRU) networks within a stacked ensemble framework, the research pioneers a composite approach that significantly outstrips the capabilities of singular models. This innovation results in a state-of-the-art system for rumor verification that outperforms accuracy in identifying rumors, as demonstrated by empirical testing and analysis. This research contributes to bridging the gap between English-centric language models and Arabic language processing, demonstrating the importance of tailored approaches for different languages in the field of ML and NLP. These contributions signify a monumental step forward in the field of Arabic NLP and ML and offer practical solutions for the real-world challenge of rumor proliferation on social media platforms, ultimately fostering a more reliable digital environment for Arabic-speaking communities.42 0Item Restricted Integrating Sentiment and Technical Analysis with Machine Learning for Improved Stock Market Predictions(University of Dundee, 2024-07-30) Almubarak, Maha Sofyan A; Mazibas, Murat; Kwiatkowski, AndrzejThis thesis advances stock forecasting by integrating sentiment analysis from Twitter as social media platform with traditional technical indicators, employing machine learning (ML) techniques. The research identifies gaps in existing literature, particularly in the use of appropriate validation methods and the balance of statistical metrics with financial benchmarks. It proposes a comprehensive methodology that incorporates Time Series Cross- Validation and hyperparameter tuning to enhance the adaptability and economic robustness of forecasting models. The empirical analysis unfolds in three chapters: 1. Technical Analysis within LSTM models to predict movements of the SPY ETF, validated through Time Series Cross-Validation to ensure robustness, focusing on both accuracy and financial performance. 2. Integration of Sentiment Analysis to assess its impact on model responsiveness and financial outcomes, demonstrating improved predictive accuracy. 3. Application to a Diverse Stock Portfolio, where models are applied to 10 different stocks across various sectors, confirming the models’ effectiveness and practical utility in real-world trading strategies. Key findings suggest that incorporating sentiment analysis significantly enhances the predictive precision of models, particularly in volatile market conditions. This synergy between technical indicators and sentiment data not only boosts accuracy but also enriches the models’ economic performance, offering valuable insights for traders and academic researchers exploring complex financial markets.10 0Item Restricted Examining Twitter as A Learning Tool on Saudi Female Undergraduate Student Achievement and Attitudes: A Mixed-Methods Study(Northern Illinois University, 2024-03-27) Bamalan, Hend; Xie, YingToday’s learners commonly belong to a generation that grew up surrounded by using technological devices in classrooms, such as smartphones, laptops, iPads, or other tools – making them digital natives. To meet the nature of digital natives’ learning needs, the focus of educational institutions has been on adapting their instructional practices to align with the new realities. In Saudi Arabia, higher education institutions were encouraged to include more instructional technology to align with the nature of digital natives and improve students’ academic performance and engagement. The use of Twitter as a learning tool in higher education is a new educational tool, grounded in the constructivist theory of learning, and serves as a promising opportunity to support the Vision 2030 initiative by improving Saudi female higher education students’ access to knowledge and participation in more expansive learning environments. It is a relatively new educational tool in Saudi higher education institutions, and empirical research that examines the effectiveness of using Twitter in the educational context is sparse. The purpose of this explanatory sequential mixed methods study was to explore the effect of using Twitter as a learning tool on undergraduate Saudi female students’ academic achievement and attitudes in a traditional academic face-to-face higher education course with a convenience sample (N=166) of two groups. One was a treatment group (n=83, Twitter as a learning tool was used), and the other was a control group (n=83, Twitter as a learning tool was not used). Quantitative data were collected using a quasi-experimental design. Qualitative data were collected via semi-structured interviews (n=8). The quantitative data were analyzed using the independent samples t-test, the paired-samples t-test, and mixed design (ANOVA) repeated measures with a between subject factors were employed to determine if there was a significant difference in academic achievement (dependent variable) between the treatment and control groups. The qualitative data explored Saudi female students’ attitudes toward using Twitter as a learning tool and were analyzed using NVivo software. The findings revealed that students who used Twitter as a learning tool had a higher academic achievement level than students who did not use Twitter as a learning tool. Moreover, students agreed that using Twitter as a learning tool provided them with opportunities to develop their interpersonal, academic, and self-confidence skills which resulted in their increased understanding and knowledge of the Digital Culture course. They also indicated that using Twitter as an educational tool allowed them to reinforce current knowledge, expand their views on the topic of discussion, encourage them to look for evidence to support their own views and respond to peers’ Tweets pertaining to their course content and field of study. In addition, students perceived that Twitter as a learning tool increased their participation and engagement in the Digital Culture course. However, most students also discussed the challenges they perceived when using Twitter for educational purposes.33 0Item Restricted Constructing the Self as a Translator: An Ethnographic Study Exploring the Saudi Translators’ Identification Processes on Twitter(Queen's University Belfast, 2024-03-27) Alkhashan, Ohud; Blumczyński, Piotr; Kaess, KathleenTwitter is one of the most popular social media platforms in Saudi Arabia, with over 12 million users. Since 2016, a growing number of translators in Saudi Arabia have been utilizing this platform to connect and interact with each other, creating a network of Saudi translators on the platform. The goal of this thesis is to explore how the Saudi translators construct their identity as professional translators on Twitter since the emergence of their network by investigating the impact of their Twitter interactions on their identification processes. To achieve this goal, the study follows a multi-sited internet ethnography where Twitter is conceptualized as an ethnographic field site for participant observation, in addition to conducting semi-structured interviews with ten Saudi professional translators from this Twitter network to gain an in-depth look into their experiences on the platform. Examining the manifestations of the concept of identification, described as a process of constructing the self by recognizing similarities and differences between the self and other during social interaction, highlights identification as processual and continuous. More specifically, the manifestations of the Saudi translators’ identification processes in their discursive practices on Twitter reflect their perceptions of visibility to one another motivated by finding a sense of belonging to a professional community for Saudi translators. This visibility fuels their perceptions of (having) power as a form of influence on the platform. Finally, (gaining) recognition of the self as a translator and translation as professional practice in Saudi Arabia is viewed as an outcome of (self-)representation practices. Exploring the Saudi translators’ identification processes on Twitter reveals the nuances in constructing a professional identity on the platform particularly in a professional network. More importantly as well, it reveals the concept’s ontological dimension as a process of becoming.17 0Item Restricted Exploring Emoji Sentiment Roles in Arabic Textual Content on Digital Social Networks(Saudi Digital Library, 2024-07-09) Hakami, Shatha Ali A; Hendley, Robert; Smith, PhillipIn today’s digital landscape, emoji have risen as pivotal elements in articulating sentiment, especially within the intricacies of the Arabic language. This thesis examines the various roles that emoji can play in expressing sentiment in Arabic texts, highlighting their relevance both in academic and real-world contexts. Beginning with foundational insights, our investigation retraces the history of emoji as important non-verbal communicative tools in human interaction. Then, we explore the distinct challenges of sentiment analysis in Arabic and refer to a thorough review of previous studies to frame our method, identifying both established techniques and unexplored opportunities. At the heart of our research is the understanding that, depending on the context, an emoji can adopt a wide variety of sentiment roles. These range from acting as an indicator, mitigator, emphasizer, reverser, releaser, or trigger of either negative or positive sentiment. Additionally, there are instances where an emoji simply maintains a neutral effect on the sentiment of the accompanying text. To achieve this, we gathered a large dataset, mainly from Twitter, and developed lexicons of words and emoji tailored for sentiment analysis in Arabic. These lexicons were the basis of our analysis model. By leveraging the insights gained from the emoji-roles sentiment lexicon and combining them with our established knowledge of the sentiment roles associated with specific emoji patterns, we make a significant improvement in the conventional sentiment classifier based on the emoji lexicon. Traditional methods often assign a static sentiment score to an emoji, failing to consider its varying roles in different textual contexts. Our refined approach corrects this oversight. Instead of considering a singular unchanging sentiment score for each emoji, the classifier dynamically retrieves sentiment scores based on the specific role the emoji plays within a given sentence. In conclusion, we compare our method with other Arabic sentiment analysis tools, demonstrating the value of our approach, especially within nuanced linguistic phenomena such as sarcasm and humour. This thesis sets the foundation for future Arabic research in this expanding domain.51 0Item Restricted Online Personas, Offline Identities: Exploring the Use of Pseudonyms Amongst Saudi Twitter Users(Saudi Digital Library, 2023-08-17) Alshehri, Razan; Cheng, ZhiIn everyday life, people present themselves depending on who their audience is. The emergence of social media platforms collapsed various audiences into one virtual space, urging users to present a unified face to everyone. To navigate that, some have resorted to the use of pseudonyms rather than their full names when they create a profile on social media. The use of pseudonyms has been an interesting phenomena that researchers have explored in the context of self-presentation and self-disclosure. However, most previous literature has focused on Western cultures when they examine the affordance of a pseudonymous self-presentation and self-disclosure. Following a socio-technical approach, this study contributes to the scarce literature on the use of pseudonyms amongst non-Western users who come from collectivist societies. The study proposes two research questions: why and how do Saudi users use pseudonyms to present themselves on Twitter. The methodology followed in this study is qualitative semi-structured interviews followed by a thematic analysis. By integrating culturally-embedded theories, affordance and anonymity, this study deduces the dual privileges that pseudonymity provides to Saudi Twitter users: 'no strings attached' and 'no questions asked' between their online personas and offline identities. Additionally, it delves into how the audience, despite the veil of pseudonymity, plays a significant role in users' self-disclosure and self-presentation dynamics. This study contributes to the information systems literature by looking at affordances and anonymity as relational concepts, providing valuable insights that unpacks the complex and socially embedded nature of these concepts. By assessing self-presentation, anonymity, and related aspects in a Saudi context, the research offers nuanced insights potentially guiding a more inclusive design and policy-making of future social media platforms.44 0Item Restricted Evaluating the impact of Twitter as a news source on the Saudi public during the COVID-19(Brunel University, 2023-11-28) Aldahmash, Hind Hamad I; Han, SamIn the contemporary era of digital technology, Twitter has emerged as one of the foremost platforms utilised by individuals as a significant online source of information. This is mostly due to its ability to provide access to a wide range of ideas, news, and original content. Twitter predominantly attracts a user base that is primarily interested in news consumption, as the platform offers features such as headline links and media tools that facilitate users' access to content. The aim of the current research is to evaluate the impact of Twitter on the Saudi public as a source of news during the COVID-19 pandemic. For this research, interview method has been taken into account in which the interviews have been conducted with 10 Saudis people aged between 18 years and 60 years. The individuals included in the sample were selected via the Twitter platform, and their agreement to participate was obtained by sending them private messages via the Twitter site. From the findings, it has been found out that the utilisation of Twitter as a news source had a significant impact on the Saudi population during the Covid-19 pandemic. Twitter has been demonstrated to be a very informative platform and an effective news medium for the population of Saudi Arabia amidst the Covid-19 pandemic. The majority of individuals in Saudi Arabia possessed Twitter accounts and actively engaged with the platform. During the Covid-19 pandemic, individuals residing in Saudi Arabia were provided with a comprehensive array of updates and information via the social media platform Twitter, encompassing both anticipated and unanticipated content.41 0Item Restricted Saudi PhD Sojourners’ Construction of Identities on Twitter: An Exploratory Study in the United Kingdom(Saudi Digital Library, 2023-11-23) Almesfer, Badryah Khaled; Satar, Muge; Brandt, AdamThis thesis provides insights into international students' online discursive construction of their identities on social media. Social media platforms have become part of the daily lives of many people. For international students, they are perhaps even more so as they are used for educational and social purposes, as well as staying in contact with family and friends at home. They are also an important way of portraying identity. Increasing numbers of students pursue university studies abroad, but little attention has been paid to how they construct and develop their international identities on social platforms, as existing research has focused primarily on pedagogical uses of technology or intercultural competence. This study explored how a group of Saudi international PhD students constructed their identities online on one of the most popular social media platforms, Twitter, while studying in the United Kingdom. It employed online ethnographic observation of Saudi PhD sojourners’ profiles and tweets on Twitter from May 2019 to January 2020, followed by interviews. The data were analysed thematically, informed by the grounded theory approach. The findings showed that the participants developed multiple identities on Twitter – PhD, global, religious and national – reflecting complex perceptions of capital, power and social identity. Their construction entailed idioms of practice, the use of linguistic and non-linguistic cues, forming communities of practice through audience design and demonstrating affiliation with various groups using hashtags. The participants illustrated how identities can be constructed online and highlighted the importance of undertaking a PhD both socially and professionally. Their interactions on Twitter also showed that the study abroad experience can be enriching in terms of intercultural communication and developing a global perspective. The study concludes that social media can be used as an effective resource for communication by students in making personal and academic representations.10 0Item Restricted SOCIAL EXCHANGE THEORY IN THE CONTEXT OF X (TWITTER) AND FACEBOOK SOCIAL MEDIA PLATFORMS WITH A FOCUS ON PRIVCAY CONCERNS AMONG SAUDI STUDENTS(Saudi Digital Library, 2023-12-16) Alqahtani, Sameer Mohammed; Prybutok, Victor RExamining rewards, costs, and comparison levels, the Social Exchange Theory (SET) in sociology underpins our comprehension of self-interest-driven social relationships. Trust, authority, and reciprocity have a substantial impact on these interactions. The Social Exchange Theory (SET) is a valuable lens for understanding human relationships, including online interactions. Social media platforms, such as X (Twitter) and Facebook, have become indispensable communication tools in our daily lives. Nevertheless, due to their user base, they also attract cybercriminals. X (Twitter) offers a variety of security features, such as password protection, two-factor authentication, privacy settings, and app controls, but users must remain vigilant against fraud attempts. Facebook collects vast amounts of private information, which increases the importance of comprehending and implementing security settings. Security awareness is essential for data protection, risk reduction, and conformance with privacy laws. Awareness allows users to manage interactions with security in mind and results in a more secure digital environment, mitigating risks such as identity fraud. Various methodological approaches have allowed the investigation of these two digital phenomena, and the current research contributes to the literature by examining the use of social media and its security settings using a SET lens within a Saudi student environment. This research followed a traditional format for a dissertation, which includes an introduction, literature review, methodology, results, and conclusion with the results section presented the findings from the three essays. The first essay employs the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology of SET. PRISMA's systematic and exhaustive approach to literature evaluation increases the likelihood of obtaining high-quality, reproducible findings. In the second essay, which focuses on awareness of X’s (Twitter) security settings, a quantitative research approach was utilized. A sample of former and current Saudi students (graduate and undergraduate) at the University of North Texas participated in the investigation. This research provides an empirical examination of the use of X (Twitter) and its security features within this community by employing statistical analysis of the data from respondents. Likewise, the same sample of Saudi students from the University of North Texas was used for the third essay in which the use of Facebook's security settings was examined. Having a consistent sample across both studies enables a comparison and a greater understanding of the security awareness and practices of this group across various social media platforms. The findings across the different studies extend our understanding of the role of culture in privacy and security concerns related to social media.56 0