Asian Journal of Information Technology
ISSN: Online 1993-5994ISSN: Print 1682-3915
Abstract
Text classification from text has gained a lot of interest in the last years, yet, some languages such as Arabic (with its different spoken dialects) has not been given such attention. In this study, we present our work in the text classification of Arabic texts with a focus on spoken Arabic dialects on Twitter messages. Therefore, we have constructed a corpus of Arabic spoken Tweets and implemented two approaches to automatically classify Tweet messages. One of the approaches uses different machine learning while the other approach uses semantic web to do the classification. Further, a comparison has been made between the two methods to determine the best configuration of the Tweets recognition system.
How to cite this article:
Mohamad Bassam Kurdy, Jamal Alnaeb and Issam Salman. Arabic Semantic Classifier of Arabic Social Media "Twitter" Users.
DOI: https://doi.org/10.36478/ajit.2019.20.27
URL: https://www.makhillpublications.co/view-article/1682-3915/ajit.2019.20.27