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Found 60 papers, 7 papers with code
MTLens: Machine Translation Output Debugging
The performance of Machine Translation (MT) systems varies significantly with inputs of diverging features such as topics, genres, and surface properties.
QADI: Arabic Dialect Identification in the Wild
For extrinsic evaluation, we are able to build effective country level dialect identification on tweets with a macro-averaged F1-score of 60. 6% across 18 classes.
Improving Arabic Text Categorization Using Transformer Training Diversification
Automatic categorization of short texts, such as news headlines and social media posts, has many applications ranging from content analysis to recommendation systems.
Creating Arabic LLM Prompts at Scale
The debut of chatGPT and BARD has popularized instruction following text generation using LLMs, where a user can interrogate an LLM using natural language requests and obtain natural language answers that matches their requests.
An Automated End-to-End Open-Source Software for High-Quality Text-to-Speech Dataset Generation
Data availability is crucial for advancing artificial intelligence applications, including voice-based technologies.
NatiQ: An End-to-end Text-to-Speech System for Arabic
We concatenated Tacotron1 with the WaveRNN vocoder, Tacotron2 with the WaveGlow vocoder and ESPnet transformer with the parallel wavegan vocoder to synthesize waveforms from the spectrograms.
Automatic Expansion and Retargeting of Arabic Offensive Language Training
Rampant use of offensive language on social media led to recent efforts on automatic identification of such language.
Cross-lingual Emotion Detection
Next, we show that using cross-lingual approaches with English data alone, we can achieve more than 90% and 80% relative effectiveness of the Arabic and Spanish BERT models respectively.
A Few Topical Tweets are Enough for Effective User Stance Detection
We show that this approach outperforms two strong baselines and achieves 89. 6{\%} accuracy and 91. 3{\%} macro F-measure on eight controversial topics.
ASAD: Arabic Social media Analytics and unDerstanding
This system demonstration paper describes ASAD: Arabic Social media Analysis and unDerstanding, a suite of seven individual modules that allows users to determine dialects, sentiment, news category, offensiveness, hate speech, adult content, and spam in Arabic tweets.
Pre-Training BERT on Arabic Tweets: Practical Considerations
The experiments highlight the centrality of data diversity and the efficacy of linguistically aware segmentation.
BERT Transformer model for Detecting Arabic GPT2 Auto-Generated Tweets
To the best of our knowledge, this work is the first study where ARABERT and GPT2 were combined to detect and classify the Arabic auto-generated texts.
Arabic Curriculum Analysis
Developing a platform that analyzes the content of curricula can help identify their shortcomings and whether they are tailored to specific desired outcomes.
A Panoramic Survey of Natural Language Processing in the Arab World
The term natural language refers to any system of symbolic communication (spoken, signed or written) without intentional human planning and design.
Political Framing: US COVID19 Blame Game
Through the use of Twitter, framing has become a prominent presidential campaign tool for politically active users.
Fighting the COVID-19 Infodemic in Social Media: A Holistic Perspective and a Call to Arms
With the outbreak of the COVID-19 pandemic, people turned to social media to read and to share timely information including statistics, warnings, advice, and inspirational stories.
Predicting the Topical Stance and Political Leaning of Media using Tweets
Discovering the stances of media outlets and influential people on current, debatable topics is important for social statisticians and policy makers.
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
Arabic Dialect Identification in the Wild
We present QADI, an automatically collected dataset of tweets belonging to a wide range of country-level Arabic dialects -covering 18 different countries in the Middle East and North Africa region.
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).
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 Few Topical Tweets are Enough for Effective User-Level Stance Detection
We show that this approach outperforms two strong baselines and achieves 89. 6% accuracy and 91. 3% macro F-measure on eight controversial topics.
Arabic Offensive Language on Twitter: Analysis and Experiments
Detecting offensive language on Twitter has many applications ranging from detecting/predicting bullying to measuring polarization.
Arabic Diacritic Recovery Using a Feature-Rich biLSTM Model
Our model surpasses all previous state-of-the-art systems with a CW error rate (CWER) of 2. 86\% and a CE error rate (CEER) of 3. 7% for Modern Standard Arabic (MSA) and CWER of 2. 2% and CEER of 2. 5% for Classical Arabic (CA).
Quantifying Polarization on Twitter: the Kavanaugh Nomination
This paper addresses polarization quantification, particularly as it pertains to the nomination of Brett Kavanaugh to the US Supreme Court and his subsequent confirmation with the narrowest margin since 1881.
Social and Information Networks J.4
A System for Diacritizing Four Varieties of Arabic
Short vowels, aka diacritics, are more often omitted when writing different varieties of Arabic including Modern Standard Arabic (MSA), Classical Arabic (CA), and Dialectal Arabic (DA).
Tanbih: Get To Know What You Are Reading
We introduce Tanbih, a news aggregator with intelligent analysis tools to help readers understanding what's behind a news story.
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
QC-GO Submission for MADAR Shared Task: Arabic Fine-Grained Dialect Identification
This paper describes the QC-GO team submission to the MADAR Shared Task Subtask 1 (travel domain dialect identification) and Subtask 2 (Twitter user location identification).
POS Tagging for Improving Code-Switching Identification in Arabic
When speakers code-switch between their native language and a second language or language variant, they follow a syntactic pattern where words and phrases from the embedded language are inserted into the matrix language.
Predicting the Topical Stance of Media and Popular Twitter Users
Discovering the stances of media outlets and influential people on current, debatable topics is important for social statisticians and policy makers.
Highly Effective Arabic Diacritization using Sequence to Sequence Modeling
Arabic text is typically written without short vowels (or diacritics).
Unsupervised User Stance Detection on Twitter
We experiment with different combinations of user similarity features, dataset sizes, dimensionality reduction methods, and clustering algorithms to ascertain the most effective and most computationally efficient combinations across three different datasets (in English and Turkish).
Social and Information Networks 62P25, 91D30
Diacritization of Maghrebi Arabic Sub-Dialects
Diacritization process attempt to restore the short vowels in Arabic written text; which typically are omitted.
Arabic Multi-Dialect Segmentation: bi-LSTM-CRF vs. SVM
Arabic word segmentation is essential for a variety of NLP applications such as machine translation and information retrieval.
Ranked #1 on
Sentiment Analysis
on DynaSent
(10 fold Cross validation metric, using extra
training data)
Learning from Relatives: Unified Dialectal Arabic Segmentation
Arabic dialects do not just share a common koin{\'e}, but there are shared pan-dialectal linguistic phenomena that allow computational models for dialects to learn from each other.
Abusive Language Detection on Arabic Social Media
We expand the list of obscene words using this classification, and we report results on a newly created dataset of classified Arabic tweets (obscene, offensive, and clean).
Arabic Diacritization: Stats, Rules, and Hacks
In this paper, we present a new and fast state-of-the-art Arabic diacritizer that guesses the diacritics of words and then their case endings.
A Neural Architecture for Dialectal Arabic Segmentation
The automated processing of Arabic Dialects is challenging due to the lack of spelling standards and to the scarcity of annotated data and resources in general.
Arabic POS Tagging: Don't Abandon Feature Engineering Just Yet
However, we show that augmenting bi-LSTM sequence labeling with some of the features that we used for the SVM-Rank based tagger yields to further improvements.
QCRI @ DSL 2016: Spoken Arabic Dialect Identification Using Textual Features
We submitted four runs to the Arabic sub-task.
Farasa: A New Fast and Accurate Arabic Word Segmenter
Meanwhile, Farasa is nearly one order of magnitude faster than QATARA and two orders of magnitude faster than MADAMIRA.
Using Stem-Templates to Improve Arabic POS and Gender/Number Tagging
This paper presents an end-to-end automatic processing system for Arabic.
Simple Effective Microblog Named Entity Recognition: Arabic as an Example
Despite many recent papers on Arabic Named Entity Recognition (NER) in the news domain, little work has been done on microblog NER.
Arabizi Detection and Conversion to Arabic
In this paper we address the problems of: identifying Arabizi in text and converting it to Arabic characters.
