Subjectivity and Sentiment Annotation of Modern Standard Arabic Newswire

Abstract

Subjectivity and sentiment analysis (SSA) is an area that has been witnessing a flurry of novel research. However, only few attempts have been made to build SSA systems for morphologically-rich languages (MRL). In the current study, we report efforts to partially bridge this gap. We present a newly labeled corpus of Modern Standard Arabic (MSA) from the news domain manually annotated for subjectivity and domain at the sentence level. We summarize our linguistically-motivated annotation guidelines and provide examples from our corpus exemplifying the different phenomena. Throughout the paper, we discuss expression of subjectivity in natural language, combining various previously scattered insights belonging to many branches of linguistics.