Key issues in conducting sentiment analysis on Arabic social media text

Abstract

The problem of extracting sentiments from text is a very complex task, in particular due to the significant amount of Natural Language Processing (NLP) required. This task becomes even more difficult when dealing with morphologically rich languages such as Modern Standard Arabic (MSA) and when processing brief, noisy texts such as “tweets” or “Facebook statuses”. This paper highlights key issues researchers are facing and innovative approaches that have been developed when performing subjectivity and sentiment analysis (SSA) on Arabic text in general and Arabic social media text in particular. A preprocessing phase to sentiment analysis is proposed and shown to noticeably improve the results of sentiment extraction from Arabic social media data.