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 linguisticallymotivated 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.
Abdul-Mageed and Diab REF present a newly labelled corpus of modern standard Arabic (MSA) from the Newswire domain.
Subjectivity and Sentiment Annotation of Modern Standard Arabic Newswire
Proceedings of the 5th Linguistic Annotation Workshop
Computer Science