Sensitivity of Arabic Sentiment Analysis Tools
Brian Conlon, Paul R. Brenner · 2020
While the accuracy of Arabic text sentiment analysis tools continues to improve, the accuracy continues to lag behind similar tools for Latin-based languages. In this work we review some of the unique challenges inherent in the Arabic language that contribute to this accuracy lag beyond the scale-based economic drivers propelling enhanced accuracy in other languages. We then identify some of the most promising new tools and provide a framework for evaluating the differences in sensitivity and polarity. While there is not yet a universal standard scale for sentiment polarity, we attempt to provide a normalized basis upon which to compare the degree to which various tools tend to classify text segments toward either end (or the middle) of the polarity spectrum.