Youssef Al Hariri

The recent growth in Middle Eastern stock markets has intensified the demand for specialized financial Arabic NLP models to serve this sector. This article presents the participation of Team SMASH of The University of Edinburgh in the Multi-dialect Intent Detection task (Subtask 1) of the Arabic Financial NLP (AraFinNLP) Shared Task 2024. The dataset used in the shared task is the ArBanking77 (Jarrar et al., 2023). We tackled this task as a classification problem and utilized several BERT and BART-based models to classify the queries efficiently. Our solution is based on implementing a two-step hierarchical classification model based on MARBERTv2. We fine-tuned the model by using the original queries. Our team, SMASH, was ranked 9th with a macro F1 score of 0.7866, indicating areas for further refinement and potential enhancement of the model’s performance.

This paper presents our submission for the Stance Detection in Arabic Language (StanceEval) 2024 shared task conducted by Team SMASH of the University of Edinburgh. We evaluated the performance of various BERT-based and large language models (LLMs). MARBERT demonstrates superior performance among the BERT-based models, achieving F1 and macro-F1 scores of 0.570 and 0.770, respectively. In contrast, Command R model outperforms all models with the highest overall F1 score of 0.661 and macro F1 score of 0.820.

Most previous research on online discussions of atheism has focused on atheism within a Christian context. In contrast, discussions about atheism in the Arab world and from Islamic background are relatively poorly studied. An added complication is that open atheism is against the law in some Arab countries, which may further restrict atheist activity on social media. In this work, we explore atheistic discussion in the Arab Twittersphere. We identify four relevant categories of Twitter users according to the content they post: atheistic, theistic, tanweeri (religious renewal), and other. We characterise the typical content posted by these four sets of users and their social networks, paying particular attention to the topics discussed and the interaction among them. Our findings have implication for the study of religious and spiritual discourse on social media and provide a better cross-cultural understanding of relevant aspects.

In this study, we investigate the extent of polarisation among theist versus atheist groups on Arab Twitter and their networks. We find four main self-identified groups of Arab users that can be distinguished by different attitudes to religion. In addition to Atheists and Theists, there are Rationalists, who promote rational thinking regardless of religious affiliation, and Tanweeri, who promote religious reforms. Through a keyword search of Twitter account handles and biographies, we identified 2,673 active, public Twitter accounts that clearly state whether they are Atheists, Theists, Tanweeri or Rationalists and analysed the interactions among themselves and the accounts that are followed, retweeted, or mentioned the most in their networks. Depending on the network analysed, we found between four and seven sub-communities that highlight the rich socio-cultural context in which discussions of religion, non-religion, and religious reform unfold. While there was clear online polarisation between atheists and theists, Rationalist and Tanweeri accounts are spread among the two polarised sides, acting as natural bridges. We also found a clear separation between Arab atheists who engage with Arab accounts promoting atheism and those who primarily engage with Western accounts promoting atheism. We discuss implications for the study of religious debate and religious polarisation on social media.

Purpose: With the upcoming COP 28 event in the United Arab Emirates, this study delves into the tweeting behavior of firms during COP events. We analyze all ESG tweets throughout COP 26 and COP 27 events, aiming to unravel the intricate connections between social media communication, industry characteristics, and financial performance. Design/methodology/approach: this study adopts a grounded theory approach to gain insights into the ESG and sustainability-focused initiatives undertaken by companies on social media, with a specific focus on the discourse surrounding climate change issues. Employing social media analytics, we conducted an in-depth analysis of ESG-related tweets from S&P 500 firms to discern the nature of their reporting and examine potential correlations with financial performance using the higher Cumulative Abnormal Returns (CARs) model.Findings: Our research findings introduce four novel distinct groups—Unengaged, Catalysts, Cautious, and Shapers—based on firms’ proactive or reactive sustainability communication patterns. Our results explore the potential impact of COP event locations on tweeting behavior, proposing that conferences held in different regions, such as Asia versus Europe, may elicit varied reactions from S&P 500 firms. In terms of legitimacy, the study finds no significant differences in tweeting characteristics between industries. However, it uncovers a correlation between firms’ CARs and their membership in specific tweeting groups, emphasizing that financial performance is intricately linked to social media communication patterns. The results challenge the simplistic view that higher social media engagement leads to positive financial outcomes, suggesting instead that lower financial performance may drive firms to adopt more extreme communication patterns, possibly as a strategic move to enhance corporate legitimacy.