Work

Arabic Opinion Mining Using Machine Learning Techniques: Algerian Dialect as a Case of Study

Year: 2022

Type: conference-paper

Abstract: Social networking services such as Facebook, Twitter, and YouTube are fertile ground for analyzing texts, extracting opinions, and identifying feelings, due to a large number of texts and their diversity in all areas of life. In this manuscript, we apply four algorithms to classify tweets written in the Algerian dialect. To extract feelings, we used six features based on three polarities. In the presented work, we manually annotate a corpus of 2,891 texts and create an Algerian lexicon of idioms that contains 1328 annotated words. Our results show that there are improvements gained in the accuracy of the system, where we have achieved a better accuracy of 85.31.

Source: International Conference on Future Networks and Distributed Systems (ICFNDS)

DOI: 10.1145/3584202.3584216

Authors: Mostefa Kara, Abdelkader Laouid, Ahcene Bounceur, Omar Aldabbas

Institutions: University of Eloued, Centre National de la Recherche Scientifique, Université de Bretagne Occidentale, Al-Balqa Applied University

Language: English

Topic: Sentiment Analysis and Opinion Mining

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

OpenAlex ID: W4376055747

FWCI: 0.827

Cites: 19

Cited by: 6

Related to: 10