Publications

2024

1. SMASH at AraFinNLP2024: Benchmarking Arabic BERT Models on the Intent Detection

   Youssef Al Hariri, and Ibrahim Abu Farha

   In Proceedings of The Second Arabic Natural Language Processing Conference , Aug 2024

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   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.

2. SMASH at StanceEval 2024: Prompt Engineering LLMs for Arabic Stance Detection

   Youssef Al Hariri, and Ibrahim Abu Farha

   In Proceedings of The Second Arabic Natural Language Processing Conference , Aug 2024

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   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.

3. Sustainability tweeting triumphs during the COP events: analyzing environmental, social, and governance (ESG) communication on Twitter

   Amr El Alfy , John Quigley , Leilei Tang , and 2 more authors

   Mar 2024

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   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.

2021

1. Atheists versus Theists: Religious Polarisation in Arab Online Communities

   Youssef Al Hariri, Walid Magdy , and Maria K. Wolters

   Proc. ACM Hum.-Comput. Interact., Oct 2021

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   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.

2019

1. Arabs and Atheism: Religious Discussions in the Arab Twittersphere

   Youssef Al Hariri, Walid Magdy , and Maria Wolters

   In Social Informatics , Oct 2019

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   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.

2. A Reconfigurable Multipurpose System on Chip Platform for Metal Detection

   Naram Mhaisen , Omran Abazeed , Youssef Al-Hariri , and 2 more authors

   In 2019 IEEE 10th GCC Conference & Exhibition (GCC) , Oct 2019

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   Modern day robotics is fast developing and evolving in various areas of multi sensor applications like body sensor networks and mine detection. A flexible platform that can be easily integrated into variety of sensors is very essential in any complex environment. A reconfigurable hardware provides a suitable platform to identify and improve existing models used in metal detection industry. In this paper, we propose and implement a metal detection module using Terasic Spider Robot, planned to be used in landmine detection operations. A hardware circuit model to detect metal was designed for the metal detection module and embedded on the TSR. The on board control system was implemented using a reconfigurable DE0 Nano System on Chip platform that can further process the information from the metal detector using efficient algorithm. The movement of the TSR was controlled remotely by Bluetooth using a smartphone app designed specifically for this application. The design also intimates the user with a message on detecting the metal. The design was implemented successfully and the metal detection module detected buried metals at a depth of maximum 7cm.

2018

1. Self-Powered IoT-Enabled Water Monitoring System

   Naram Mhaisen , Omran Abazeed , Youssef Al Hariri , and 2 more authors

   In 2018 International Conference on Computer and Applications (ICCA) , Oct 2018

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   While usable water on earth is sparse and costly to treat, statistics show excessive use worldwide. Penalties are issued to limit the excessive consumption; however, their impact is marginal as they do not identify the reason for the exorbitant consumption. Therefore, giving users the full awareness about their water consumption will greatly help in minimizing the water waste. This article aims to present a smart self-powered water monitoring system that leverages IoT and cloud computing. The system consists of an IoT device that can be installed at any water source, a cloud application to receive the data from the devices, and a mobile app to visualize the water consumption at every monitored source. This system gives the user the ability to identify the location and time of the excessive usage and leaks on the mobile phone. Experiment results confirm the self-powered premise of the solution. A prototype of mobile application and backend have been developed and tested.

2015

1. Teaching Database Management Systems in Higher Education: An Efficient Approach for Introductory Courses

   Osama Shata , Naram Mhaisen , Omran Abazeed , and 1 more author

   Nov 2015

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   The software tool used for teaching database courses plays an essential role in the learning process and its outcome. It enables students to implement the concepts of database and transfer it into real word applications. This paper examine two of the most famous Database Management Systems: Oracle Database, and Microsoft Access. The examination will aim to identify the most suitable software that should be used to introduce the students into the database concepts. Both Database Management Systems are explored and compared based on analysis of a survey results.