1 code implementation • EACL (WANLP) 2021 • Zien Sheikh Ali, Watheq Mansour, Tamer Elsayed, Abdulaziz Al‐Ali
We introduce AraFacts, the first large Arabic dataset of naturally occurring claims collected from 5 Arabic fact-checking websites, e. g., Fatabyyano and Misbar, and covering claims since 2016.
no code implementations • OSACT (LREC) 2022 • Rana Malhas, Watheq Mansour, Tamer Elsayed
Moreover, we outline the main approaches adopted by the participating teams in the context of highlighting some of our perceptions and general trends that characterize the participating systems and their submitted runs.
1 code implementation • OSACT (LREC) 2022 • Zien Sheikh Ali, Abdulaziz Al-Ali, Tamer Elsayed
We construct an Arabic dataset on Twitter users, which consists of 1, 546 users, of which 541 are prone to spread fake news (based on our definition).
1 code implementation • 10 Mar 2024 • Watheq Mansour, Salam Albatarni, Sohaila Eltanbouly, Tamer Elsayed
Although several methods were proposed to address the problem of automated essay scoring (AES) in the last 50 years, there is still much to desire in terms of effectiveness.
1 code implementation • 14 Jan 2023 • Fatima Haouari, Tamer Elsayed
We believe the task is useful to augment the sources of evidence utilized by existing rumor verification systems.
no code implementations • 9 Nov 2022 • Maram Hasanain, Tamer Elsayed
Our results show that for some language pairs, zero-shot cross-lingual transfer is possible and can perform as good as monolingual models that are trained on the target language.
no code implementations • 23 Jul 2022 • Dilara Dogan, Bahadir Altun, Muhammed Said Zengin, Mucahid Kutlu, Tamer Elsayed
Our experiments show that the performance of BERT-based models fined tuned for stance detection decreases significantly due to typos, but it is not affected by paraphrasing.
no code implementations • 25 Sep 2021 • Tamer Elsayed, Preslav Nakov, Alberto Barrón-Cedeño, Maram Hasanain, Reem Suwaileh, Giovanni Da San Martino, Pepa Atanasova
We present an overview of the second edition of the CheckThat!
no code implementations • 23 Sep 2021 • Preslav Nakov, Giovanni Da San Martino, Tamer Elsayed, Alberto Barrón-Cedeño, Rubén Míguez, Shaden Shaar, Firoj Alam, Fatima Haouari, Maram Hasanain, Watheq Mansour, Bayan Hamdan, Zien Sheikh Ali, Nikolay Babulkov, Alex Nikolov, Gautam Kishore Shahi, Julia Maria Struß, Thomas Mandl, Mucahid Kutlu, Yavuz Selim Kartal
We describe the fourth edition of the CheckThat!
no code implementations • 13 Mar 2021 • Preslav Nakov, David Corney, Maram Hasanain, Firoj Alam, Tamer Elsayed, Alberto Barrón-Cedeño, Paolo Papotti, Shaden Shaar, Giovanni Da San Martino
The reporting and the analysis of current events around the globe has expanded from professional, editor-lead journalism all the way to citizen journalism.
no code implementations • COLING 2020 • Reem Suwaileh, Muhammad Imran, Tamer Elsayed, Hassan Sajjad
For example, results show that, for training a location mention recognition model, Twitter-based data is preferred over general-purpose data; and crisis-related data is preferred over general-purpose Twitter data.
no code implementations • EACL (WANLP) 2021 • Fatima Haouari, Maram Hasanain, Reem Suwaileh, Tamer Elsayed
In this paper we introduce ArCOV19-Rumors, an Arabic COVID-19 Twitter dataset for misinformation detection composed of tweets containing claims from 27th January till the end of April 2020.
3 code implementations • 15 Jul 2020 • Alberto Barron-Cedeno, Tamer Elsayed, Preslav Nakov, Giovanni Da San Martino, Maram Hasanain, Reem Suwaileh, Fatima Haouari, Nikolay Babulkov, Bayan Hamdan, Alex Nikolov, Shaden Shaar, Zien Sheikh Ali
The first four tasks compose the full pipeline of claim verification in social media: Task 1 on check-worthiness estimation, Task 2 on retrieving previously fact-checked claims, Task 3 on evidence retrieval, and Task 4 on claim verification.
1 code implementation • 19 May 2020 • Ammar Rashed, Mucahid Kutlu, Kareem Darwish, Tamer Elsayed, Cansin Bayrak
On June 24, 2018, Turkey conducted a highly consequential election in which the Turkish people elected their president and parliament in the first election under a new presidential system.
Ranked #1 on Stance Detection on Trump Midterm Elections 2018
no code implementations • LREC 2020 • Hamdy Mubarak, Kareem Darwish, Walid Magdy, Tamer Elsayed, Hend Al-Khalifa
This paper provides an overview of the offensive language detection shared task at the 4th workshop on Open-Source Arabic Corpora and Processing Tools (OSACT4).
no code implementations • LREC 2020 • Abeer Abuzayed, Tamer Elsayed
To tackle the problem efficiently, we adopt a {``}quick and simple{''} approach by which we investigate the effectiveness of 15 classical (e. g., SVM) and neural (e. g., CNN) learning models, while exploring two different term representations.
1 code implementation • EACL (WANLP) 2021 • Fatima Haouari, Maram Hasanain, Reem Suwaileh, Tamer Elsayed
In this paper, we present ArCOV-19, an Arabic COVID-19 Twitter dataset that spans one year, covering the period from 27th of January 2020 till 31st of January 2021.
3 code implementations • 21 Jan 2020 • Alberto Barron-Cedeno, Tamer Elsayed, Preslav Nakov, Giovanni Da San Martino, Maram Hasanain, Reem Suwaileh, Fatima Haouari
Finally, the lab offers a fifth task that asks to predict the check-worthiness of the claims made in English political debates and speeches.
no code implementations • 23 Sep 2019 • Mucahid Kutlu, Kareem Darwish, Cansin Bayrak, Ammar Rashed, Tamer Elsayed
During the election period, the Turkish people extensively shared their political opinions on Twitter.
Social and Information Networks
no code implementations • WS 2019 • Sohaila Eltanbouly, May Bashendy, Tamer Elsayed
This paper presents the participation of Qatar University team in MADAR shared task, which addresses the problem of sentence-level fine-grained Arabic Dialect Identification over 25 different Arabic dialects in addition to the Modern Standard Arabic.
no code implementations • 17 Jan 2018 • Md Mustafizur Rahman, Mucahid Kutlu, Tamer Elsayed, Matthew Lease
To create a new IR test collection at low cost, it is valuable to carefully select which documents merit human relevance judgments.
no code implementations • SEMEVAL 2017 • Marwan Torki, Maram Hasanain, Tamer Elsayed
In this paper we describe our QU-BIGIR system for the Arabic subtask D of the SemEval 2017 Task 3.