Paper: Subjectivity and Sentiment Analysis of Modern Standard Arabic

ACL ID P11-2103
Title Subjectivity and Sentiment Analysis of Modern Standard Arabic
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2011
Authors

Although Subjectivity and Sentiment Analysis (SSA) has been witnessing a flurry of novel re- search, there are few attempts to build SSA systems for Morphologically-Rich Languages (MRL). In the current study, we report efforts to partially fill this gap. We present a newly developed manually annotated corpus of Mod- ern Standard Arabic (MSA) together with a new polarity lexicon.The corpus is a collec- tion of newswire documents annotated on the sentence level. We also describe an automatic SSA tagging system that exploits the anno- tated data. We investigate the impact of differ- ent levels of preprocessing settings on the SSA classification task. We show that by explicitly accounting for the rich morphology the system is able to achieve significantly higher levels of performance.