ArabiziVec: A Set of ArabiziWord Embeddings for Informal Arabic Sentiment Analysis

Abstract

The current circumstances of the Arab world have provided bloggers and commenters with various subjects to discuss. Therefore, Arabic-generated content in social media is ramping up continuously. An informal written form of spoken Arabic called Arabizi has recently emerged as a commonly used language in the Arabic space, attracting great interest for sentiment analysis tasks. However, only a few sentiment resources exist, and state-of-the-art language models such as BERT and FastText do not consider Arabizi yet. This paper presents the first version of ArabiziVec, a set of pre-trained distributed word representations. ArabiziVec provides six different word embedding models to deal with Arabizi sentiment analysis challenges. The presented work surpasses all of the baseline sets for each experiment, regardless of whether the test set is from a previously published dataset or an extracted one. To the best of our knowledge, this is one of the first few resources that deals with Arabizi content and semantics in the context of sentiment analysis