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Found 38 papers, 6 papers with code
Overview of the WANLP 2021 Shared Task on Sarcasm and Sentiment Detection in Arabic
This paper provides an overview of the WANLP 2021 shared task on sarcasm and sentiment detection in Arabic.
UPV at the Arabic Hate Speech 2022 Shared Task: Offensive Language and Hate Speech Detection using Transformers and Ensemble Models
This paper describes our participation in the shared task Fine-Grained Hate Speech Detection on Arabic Twitter at the 5th Workshop on Open-Source Arabic Corpora and Processing Tools (OSACT).
DTW at Qur’an QA 2022: Utilising Transfer Learning with Transformers for Question Answering in a Low-resource Domain
The goal of the Qur’an QA 2022 shared task is to fill this gap by producing state-of-the-art question answering and reading comprehension research on Qur’an.
Chinese Offensive Language Detection:Current Status and Future Directions
Despite the considerable efforts being made to monitor and regulate user-generated content on social media platforms, the pervasiveness of offensive language, such as hate speech or cyberbullying, in the digital space remains a significant challenge.
Pushing Boundaries: Exploring Zero Shot Object Classification with Large Multimodal Models
To bolster our analysis, we assess the model's performance post fine-tuning for specific tasks.
Can ChatGPT be Your Personal Medical Assistant?
This study aims to evaluate the potential of using a fine-tuned ChatGPT model as a personal medical assistant in the Arabic language.
ArAIEval Shared Task: Persuasion Techniques and Disinformation Detection in Arabic Text
We present an overview of the ArAIEval shared task, organized as part of the first ArabicNLP 2023 conference co-located with EMNLP 2023.
Transformers and Ensemble methods: A solution for Hate Speech Detection in Arabic languages
This paper describes our participation in the shared task of hate speech detection, which is one of the subtasks of the CERIST NLP Challenge 2022.
Overview of the WANLP 2022 Shared Task on Propaganda Detection in Arabic
Thus, there has been a lot of recent research on automatic detection of propaganda techniques in text as well as in memes.
DTW at Qur'an QA 2022: Utilising Transfer Learning with Transformers for Question Answering in a Low-resource Domain
The goal of the Qur'an QA 2022 shared task is to fill this gap by producing state-of-the-art question answering and reading comprehension research on Qur'an.
Findings of the NLP4IF-2021 Shared Tasks on Fighting the COVID-19 Infodemic and Censorship Detection
Here, we present the tasks, analyze the results, and discuss the system submissions and the methods they used.
Political Framing: US COVID19 Blame Game
Through the use of Twitter, framing has become a prominent presidential campaign tool for politically active users.
Building a Corpus of Qatari Arabic Expressions
The current Arabic natural language processing resources are mainly build to address the Modern Standard Arabic (MSA), while we witnessed some scattered efforts to build resources for various Arabic dialects such as the Levantine and the Egyptian dialects.
DAICT: A Dialectal Arabic Irony Corpus Extracted from Twitter
Identifying irony in user-generated social media content has a wide range of applications; however to date Arabic content has received limited attention.
Fighting the COVID-19 Infodemic: Modeling the Perspective of Journalists, Fact-Checkers, Social Media Platforms, Policy Makers, and the Society
With the emergence of the COVID-19 pandemic, the political and the medical aspects of disinformation merged as the problem got elevated to a whole new level to become the first global infodemic.
A Fine-Grained Annotated Multi-Dialectal Arabic Corpus
We present ARAP-Tweet 2. 0, a corpus of 5 million dialectal Arabic tweets and 50 million words of about 3000 Twitter users from 17 Arab countries.
MADARi: A Web Interface for Joint Arabic Morphological Annotation and Spelling Correction
In this paper, we introduce MADARi, a joint morphological annotation and spelling correction system for texts in Standard and Dialectal Arabic.
Arap-Tweet: A Large Multi-Dialect Twitter Corpus for Gender, Age and Language Variety Identification
In this paper, we present Arap-Tweet, which is a large-scale and multi-dialectal corpus of Tweets from 11 regions and 16 countries in the Arab world representing the major Arabic dialectal varieties.
Guidelines and Annotation Framework for Arabic Author Profiling
In this paper, we present the annotation pipeline and the guidelines we wrote as part of an effort to create a large manually annotated Arabic author profiling dataset from various social media sources covering 16 Arabic countries and 11 dialectal regions.
Critical Survey of the Freely Available Arabic Corpora
Currently, there is not easy was to access to a comprehensive and updated list of freely available Arabic corpora.
Using Ambiguity Detection to Streamline Linguistic Annotation
Arabic writing is typically underspecified for short vowels and other markups, referred to as diacritics.
Guidelines and Framework for a Large Scale Arabic Diacritized Corpus
This paper presents the annotation guidelines developed as part of an effort to create a large scale manually diacritized corpus for various Arabic text genres.
Applying the Cognitive Machine Translation Evaluation Approach to Arabic
The goal of the cognitive machine translation (MT) evaluation approach is to build classifiers which assign post-editing effort scores to new texts.
Building an Arabic Machine Translation Post-Edited Corpus: Guidelines and Annotation
We present our guidelines and annotation procedure to create a human corrected machine translated post-edited corpus for the Modern Standard Arabic.
Large Scale Arabic Error Annotation: Guidelines and Framework
Finally, we present the annotation tool that was developed as part of this project, the annotation pipeline, and the quality of the resulting annotations.
Can Crowdsourcing be used for Effective Annotation of Arabic?
Crowdsourcing has been used recently as an alternative to traditional costly annotation by many natural language processing groups.
