Building Arabic Polarizerd Lexicon from Rated Online Customer Reviews
Mohammad Daoud · 2017
Building a polarized lexicon is an essential step towards a reliable opinion mining engine. In this paper we are presenting an approach and describing an experiment to build an Arabic polarized lexicon from analyzing online customer reviews. These reviews are written in Modern Standard Arabic and Palestinian/Jordanian dialect. Therefore, the produced lexicon compromises casual slangs and dialectic entries used by the online community, which is useful for sentiment analysis of informal social media microblogs. We have extracted 28000 entries from processing 15100 reviews and by expanding the initial lexicon with through google translate. Each entry was given a polarity tag and a confidence score. High confidence scores have increased the precision of the polarization process.