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Found 9 papers, 1 papers with code
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.
ASU\_OPTO at OSACT4 - Offensive Language Detection for Arabic text
In the past years, toxic comments and offensive speech are polluting the internet and manual inspection of these comments is becoming a tiresome task to manage.
A Simple and Effective Approach for Fine Tuning Pre-trained Word Embeddings for Improved Text Classification
This work presents a new and simple approach for fine-tuning pretrained word embeddings for text classification tasks.
Combining Lexical Features and a Supervised Learning Approach for Arabic Sentiment Analysis
The importance of building sentiment analysis tools for Arabic social media has been recognized during the past couple of years, especially with the rapid increase in the number of Arabic social media users.
NileTMRG at SemEval-2017 Task 4: Arabic Sentiment Analysis
The authors participated in three Arabic related subtasks which are: Subtask A (Message Polarity Classification), Sub-task B (Topic-Based Message Polarity classification) and Subtask D (Tweet quantification) using the team name of NileTMRG.
NileTMRG at SemEval-2017 Task 8: Determining Rumour and Veracity Support for Rumours on Twitter.
Final submission for NileTMRG on RumourEval 2017.
NileULex: A Phrase and Word Level Sentiment Lexicon for Egyptian and Modern Standard Arabic
To demonstrate that a lexicon such as this can directly impact the task of sentiment analysis, a very basic machine learning based sentiment analyser that uses unigrams, bigrams, and lexicon based features was applied on two different Twitter datasets.
