Please use this identifier to cite or link to this item:
https://dspace.univ-ouargla.dz/jspui/handle/123456789/28498
Title: | Sentiment Analysis in Arabic Tweets |
Authors: | Israr, BERRIM wafa, SAADI |
Keywords: | Social Big Data, Sentiment Analysis, Natural Language Processing, Machine Learning, Algerian Dialectal Arabic, Twitter, Random Forest. Méga Données Sociaux, L’analyse des sentiments, Traitement du langage naturel, apprentissage automatique, Arabe Dialectal Algérienne, Twitter, Random Forest |
Issue Date: | 2020 |
Publisher: | UNIVERSITY OF KASDI MERBAH OUARGLA |
Abstract: | Sentiment analysis is one of the most active research areas in natural language processing in recent years. It is the computational study of sentiments and emotions expressed in written human languages. While emotions are central to almost all human activities, especially in Social Media, social big data becomes one of the most important source of data for sentiment analysis. This work consists in developing a platform that presents our contribution in the field of classification of the polarity (Positive/Negative) by using machine learning techniques (classification model) and a generated database. This last is consisted of Twitter comments or “tweets” written in both Modern Standard Arabic (MSA) and Algerian Dialectal Arabic. For the favour of the sentiment analysis field, in our work we fortunately managed the use of Random Forest learning model. |
URI: | http://dspace.univ-ouargla.dz/jspui/handle/123456789/28498 |
Appears in Collections: | Département d'informatique et technologie de l'information - Master |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
BERRIM-Israr_.pdf | 823,53 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.