SAMAR: Subjectivity and sentiment analysis for Arabic social media ?
We present a system for subjectivity and sentiment analysis (SSA) for Arabic social media data. Individual settings are required per genre and task. Using either lemmas or lexemes improves SSA results. Using a POS tagset leads improved results, as do standard features. Processing dialects does not improve when it is know which sentences are in dialect. Genre specific features tend to be helpful for sentiment analysis, but not for subjectivity.
subjectivity and sentiment analysis arabic social media data morphologically rich language