| 2 |
Automatic Identification of Maghreb Dialects Using a Dictionary-Based Approach
|
|
|
|
In: Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018) ; Eleventh International Conference on Language Resources and Evaluation (LREC 2018) ; https://hal.archives-ouvertes.fr/hal-02012150 ; Eleventh International Conference on Language Resources and Evaluation (LREC 2018), May 2018, Miyazaki, Japan (2018)
|
|
BASE
|
|
Show details
|
|
|
| 3 |
Statistical Machine Translation: Application to low resourced languages ; Traduction Automatique Fondée sur des Méthodes Statistiques : Application aux Langues peu Dotées en Ressources
|
|
|
|
In: https://hal.inria.fr/tel-03186940 ; Computation and Language [cs.CL]. École Supérieure d’Informatique, 2018. English (2018)
|
|
BASE
|
|
Show details
|
|
|
| 4 |
La communication entre Libanais et Jordaniens sur les réseaux numériques ; Communication Practices Between Lebanese and Jordanians on Digital Networks
|
|
|
|
In: Hermès [ISSN 0767-9513], Nouvelles voix de la recherche en communication, 2018, 82, p. 216 (2018)
|
|
BASE
|
|
Show details
|
|
|
| 5 |
A Multitask-Based Neural Machine Translation Model with Part-of-Speech Tags Integration for Arabic Dialects
|
|
|
|
In: Applied Sciences ; Volume 8 ; Issue 12 (2018)
|
|
BASE
|
|
Show details
|
|
|
| 8 |
Dataset construction for the detection of anti-social behaviour in online communication in arabic
|
|
|
|
Abstract:
peer-reviewed ; Warning: this paper contains a range of words which may cause offence. In recent years, many studies target anti-social behaviour such as offensive language and cyberbullying in online communication. Typically, these studies collect data from various reachable sources, the majority of the datasets being in English. However, to the best of our knowledge, there is no dataset collected from the YouTube platform targeting Arabic text and overall there are only a few datasets of Arabic text, collected from other social platforms for the purpose of offensive language detection. Therefore, in this paper we contribute to this field by presenting a dataset of YouTube comments in Arabic, specifically designed to be used for the detection of offensive language in a machine learning scenario. Our dataset contains a range of offensive language and flaming in the form of YouTube comments. We document the labelling process we have conducted, taking into account the difference in the Arab dialects and the diversity of perception of offensive language throughout the Arab world. Furthermore, statistical analysis of the dataset is presented, in order to make it ready for use as a training dataset for predictive modelling.
|
|
Keyword:
Anti-social behaviour online; Arabic dataset; Arabic dialects; harassment detection; offensive language; text classification; text mining
|
|
URL: http://hdl.handle.net/10344/7878
https://doi.org/10.1016/j.procs.2018.10.473
|
|
BASE
|
|
Hide details
|
|
|
| 9 |
Algunos proverbios de actual uso en Damasco ; Some proverbs in current use in Damascus
|
|
|
|
In: Dialectologia: revista electrònica; 2018: Núm. 20; p. 43-60 (2018)
|
|
BASE
|
|
Show details
|
|
|
|
|
