The increase of the user-generated content on the web led to the explosion of opinionated text which facilitated opinion mining research. Despite the popularity of this research field in English text and the large number of Arabic speakers who contribute continuously to the web content, Arabic opinion mining has not received much attention due to the lack of reliable NLP tools and an accepted/comprehensive dataset. While English opinion mining has been studied extensively, Arabic opinion mining hasnโt received as much attention. The work that exists in sentiment analysis is limited to news, blogs written in Modern Standard Arabic and few studies on social media and web reviews written in Arabic dialect. Moreover, most of the work done has been done at the document and sentence level and to best of our knowledge, there is no work on a more fine-grained level. In this work, we take a more fine-grained approach to Arabic opinion mining at the aspect level through experimentation with methods that have been used in English Aspect extraction. Further, we are also contributing a dataset that can be used for further research on Arabic dialect
