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Found 24 papers, 8 papers with code
QU-BIGIR at SemEval 2017 Task 3: Using Similarity Features for Arabic Community Question Answering Forums
In this paper we describe our QU-BIGIR system for the Arabic subtask D of the SemEval 2017 Task 3.
Efficient Test Collection Construction via Active Learning
To create a new IR test collection at low cost, it is valuable to carefully select which documents merit human relevance judgments.
Simple But Not Na\"\ive: Fine-Grained Arabic Dialect Identification Using Only N-Grams
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.
Embedding-based Qualitative Analysis of Polarization in Turkey
During the election period, the Turkish people extensively shared their political opinions on Twitter.
Social and Information Networks
CheckThat! at CLEF 2020: Enabling the Automatic Identification and Verification of Claims in Social Media
Finally, the lab offers a fifth task that asks to predict the check-worthiness of the claims made in English political debates and speeches.
ArCOV-19: The First Arabic COVID-19 Twitter Dataset with Propagation Networks
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.
Quick and Simple Approach for Detecting Hate Speech in Arabic Tweets
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.
Overview of OSACT4 Arabic Offensive Language Detection Shared Task
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).
Embeddings-Based Clustering for Target Specific Stances: The Case of a Polarized Turkey
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
Overview of CheckThat! 2020: Automatic Identification and Verification of Claims in Social Media
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.
ArCOV19-Rumors: Arabic COVID-19 Twitter Dataset for Misinformation Detection
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.
Are We Ready for this Disaster? Towards Location Mention Recognition from Crisis Tweets
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.
Automated Fact-Checking for Assisting Human Fact-Checkers
The reporting and the analysis of current events around the globe has expanded from professional, editor-lead journalism all the way to citizen journalism.
Overview of the CLEF--2021 CheckThat! Lab on Detecting Check-Worthy Claims, Previously Fact-Checked Claims, and Fake News
We describe the fourth edition of the CheckThat!
Overview of the CLEF-2019 CheckThat!: Automatic Identification and Verification of Claims
We present an overview of the second edition of the CheckThat!
Catch Me If You Can: Deceiving Stance Detection and Geotagging Models to Protect Privacy of Individuals on Twitter
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.
Cross-lingual Transfer Learning for Check-worthy Claim Identification over Twitter
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.
Detecting Stance of Authorities towards Rumors in Arabic Tweets: A Preliminary Study
We believe the task is useful to augment the sources of evidence utilized by existing rumor verification systems.
Can Large Language Models Automatically Score Proficiency of Written Essays?
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.
AraFacts: The First Large Arabic Dataset of Naturally Occurring Claims
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.
Detecting Users Prone to Spread Fake News on Arabic Twitter
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).
Qur’an QA 2022: Overview of The First Shared Task on Question Answering over the Holy Qur’an
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.
