Feature-Based Sentiment Analysis for Arabic Language

Abstract

In light of the spread of e-commerce and emarketing, and the presence of a huge number of reviews and texts written by people to share views on products, it became necessary to give attention to extracting these opinions automatically and analyzing the feelings of the reviewers. The goal is to obtain reports evaluating products and contribute to improve services at a glance. Sentiment Analysis is a relatively recent study that deals with the processing of natural texts published in web sites and social networks. However, the processing of texts written in the Arabic language is one of the challenges that specialists face because people do not rely on standard Arabic, writing people in spoken/colloquial languages and use various dialects. This paper will present feature-based sentiment analysis for Arabic language which works on text analysis technique that breaks down text into aspects (attributes or components of a product or service), and then allocates each one a sentiment level (positive, negative or neutral).

Sentiment Analysis of Smartphone Accounting Application Users

“…The review mining method used in this study implements the Feature-Based Summarization (FBS) by (M. Hu & Bing, 2004;Widyassari et al, 2020). The FBS method has been implemented by many previous studies (Alhamad & Kurdy, 2020;Choudhary & Arora, 2021;Guerrero, Chiclana, Olivas, Romero, & Homapour, 2020). Figure 1 shows the flow of review mining techniques using FBS.…”