Aspects Detection Model for Users’ Reviews Using Machine Learning Techniques

Document Type : Original Article

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Information System , Computers and Artificial Intelligence , Helwan , Cairo ,Egypt

Abstract

Sentiment analysis (SA) is an important field that is concerned with capturing user emotions, mode and interests through a written text. sentiment analysis (SA) and opinion mining has become a trendy topic today it helps us to catch the emotions of the speaker whether sad or happy etc.. As well as some government may use this field to catch the emotions of their people whether they satisfied about their way they use to control the country or not. The number of people use social media is rapidly increasing because many people use it to share their opinions, feeling and emotions so that social media platforms like twitter or Facebook possess a large volume of data for example lots of tweets are posted on twitter every day, that can be analyzed in order to capturing the current state or mode of the author. Currently in the age of corona many companies obliged their employees to work from home millions of tweets are posted people uses this platform to share their opinion, feeling and their new lifestyle during quarantine. The volume of data become larger and it became a fertile material for analysis to know how people feel and how they adapt to the new situation. The research objective is to provide a review of using aspect-based sentiment analysis to detect user satisfaction , and applying this technique on such a trendy topic, which is working from home during covide pandemic. In addition to detecting problems they face .

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