Analyzing user opinions has always been an integral part of information processing and thus Sentiment Analysis has been a very active research area since the last decade. Sentiment Analysis is done at different levels of granularity ranging from coarse grained Document level to fine grained Aspect Level. In this paper we describe the most granular form of analyzing opinions i.e Aspect Based Sen...

Actually, there are many approaches to deal with crosscutting concerns in early stages in software development. One is MDSOC, which promotes the encapsulation of all relevant kinds of concerns (dimensions) and their integration. MDSOC starts from an initial problem decomposition to design the system. No discussion about how this decomposition should be carried is presented. Based on this defici...

Aspect-based sentiment analysis (ABSA) is the sub-field of natural language processing that deals with breaking or splitting texts into aspects and then classification sentiments like happy, sad, angry, etc. towards aspect. provides more information about context than general analysis. In this survey paper, we compared a variety papers methods were introduced through them on achieving better re...

A sentence may express sentiments on multiple aspects. When these aspects are associated with different sentiment polarities, a model’s accuracy is often adversely affected. We observe that in such hard sentences mostly expressed through clauses, or formally known as elementary discourse units (EDUs), and one EDU tends to single aspect unitary towards aspect. In this paper, we propose consider ...

Aspect-based Sentiment analysis (ABSA) accomplishes a fine-grained that defines the aspects of given document or sentence and sentiments conveyed regarding each aspect. This level is most detailed version capable exploring nuanced viewpoints reviews. The bulk study in ABSA focuses on English with very little work available Arabic. Most previous Arabic has been based regular methods machine lear...