Publications

2024

1. TwiXplorer: An Interactive Tool for Narrative Detection and Analysis in Historic Twitter Data

   Youssef Al Hariri, Sandrine Chausson , Björn Ross , and 1 more author

   In Companion Publication of the 2024 Conference on Computer-Supported Cooperative Work and Social Computing , Nov 2024

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   We present TwiXplorer, an interactive tool to explore and understand static Twitter (X) datasets. While obtaining new data from X has become more challenging for academics, there are still rich datasets available that have largely been untapped, for example, from the "The Twitter Stream Grab” project at the Internet Archive. Accessing and exploring this historical Twitter data is crucial for researchers interested in studying the history of social media. Our system is more advanced and easy to use than existing options and demonstrates how AI can help and be integrated into a process to make sense of large datasets. The tool is accessed through a web-based dashboard and designed with interaction in mind: the analyst can iteratively explore the data instead of being presented with static reports. We make the tool fully open source.

2. 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.

3. 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.

4. 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

   Nov 2024

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   Purpose: With the recent conclusion of the United Nations Conference of the Parties (COP) 28 in the United Arab Emirates, this study aims to investigate the tweeting behaviour of firms surrounding COP events. The authors analyse the environmental, social and governance (ESG) tweets from the COP 26 and COP 27 events, aiming to deepen the understanding of the complex relationships between social media communication, industry characteristics and financial performance. This timely analysis is critical for assessing how the latest global discussions on climate change are influencing corporate communication strategies on sustainability, offering fresh insights into the evolving dynamics of ESG engagement in the context of these pivotal international meetings. Design/methodology/approach: In this study, the authors embrace a grounded theory approach to gain insights into the ESG and sustainability initiatives presented by companies on social media, with an intensified focus on climate change discourse. Leveraging advanced social media analytics, this study expands its scope by conducting a thorough examination of ESG-related tweets from Standard and Poor’s (S&P) 500 companies. In addition, the authors explore the relationships between such communication efforts and financial performance, applying an advanced cumulative abnormal returns (CARs) model. This methodological enhancement enables a more sophisticated understanding of how ESG communication on Twitter correlates with, and potentially influences, a firm’s market valuation and financial health, offering invaluable insights into the strategic importance of digital sustainability discourse. Findings: The research findings introduce four novel distinct groups – Unengaged, Catalysts, Cautious and Shapers – based on firms’ proactive or reactive sustainability communication patterns. The results explore the potential impact of COP event locations on tweeting behaviour, proposing that conferences held in different regions, such as Asia versus Europe, may elicit varied reactions from S&P 500 firms. Despite no significant inter-industry differences in tweeting habits, the authors discover a significant link between firms’ financial metrics, specifically CARs, and their categorised communication styles. 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.