no code implementations • 25 Nov 2020 • Kareem Darwish, Nizar Habash, Mourad Abbas, Hend Al-Khalifa, Huseein T. Al-Natsheh, Samhaa R. El-Beltagy, Houda Bouamor, Karim Bouzoubaa, Violetta Cavalli-Sforza, Wassim El-Hajj, Mustafa Jarrar, Hamdy Mubarak
The term natural language refers to any system of symbolic communication (spoken, signed or written) without intentional human planning and design.
no code implementations • LREC 2020 • Amr Keleg, Samhaa R. El-Beltagy, Mahmoud Khalil
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.
1 code implementation • 7 Aug 2019 • Amr Al-Khatib, Samhaa R. El-Beltagy
This work presents a new and simple approach for fine-tuning pretrained word embeddings for text classification tasks.
no code implementations • SEMEVAL 2017 • Samhaa R. El-Beltagy, Mona El Kalamawy, Abu Bakr Soliman
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.
no code implementations • 23 Oct 2017 • Samhaa R. El-Beltagy, Talaat Khalil, Amal Halaby, Muhammad Hammad
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.
no code implementations • SEMEVAL 2017 • Omar Enayet, Samhaa R. El-Beltagy
Final submission for NileTMRG on RumourEval 2017.
no code implementations • LREC 2016 • Samhaa R. El-Beltagy
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.