Use of Arabic sentiment analysis for mobile applications’ requirements evolution: Trends and challenges

Abstract

The rapidly increasing volume of reviews for the different mobile applications (apps) makes it almost impossible to analyze user feedback reviews manually. Reviews can contain star ratings, emotions, and text reviews for a proposed feature, a bug report, and/or a confidentiality protest. Stakeholders can benefit from reviews after analyzing them using Sentiment Analysis (SA) as user requirements, ideas for improvements, user sentiments about specific features, and descriptions of experiences with these features. This paper investigates the field of research of using Arabic SA for mobile apps’ requirements evolution. We assembled answers from the literature for four Research Questions (RQs) we formulated. The results revealed three main points. First, the use of SA trends in general for mobile apps’ requirements evolution research can be grouped to automating extraction of future requirements, applying ranking frameworks to classify reviews to informative and non-informative, and proposing visualization techniques for users’ feedback. Second, there turned to be many current challenges that face the field of using Arabic SA for user comments of mobile apps’ requirements evolution because of the inherent challenges of three intersecting fields. Finally, there is little proof that there is any study conducted till now that applies the use of Arabic SA on user comments of mobile apps for the purpose of requirements evolution.