SenZi: A Sentiment Analysis Lexicon for the Latinised Arabic (Arabizi)
Taha Tobaili, Miriam Fernández, Harith Alani, Sanaa Sharafeddine, Hazem M. Hajj, Goran Glavaš, Data and Web Science Group, Universität Mannheim, Germany · 2019
Arabizi is an informal written form of dialectal Arabic transcribed in Latin alphanumeric characters.It has a proven popularity on chat platforms and social media, yet it suffers from a severe lack of natural language processing (NLP) resources.As such, texts written in Arabizi are often disregarded in sentiment analysis tasks for Arabic.In this paper we describe the creation of a sentiment lexicon for Arabizi that was enriched with word embeddings.The result is a new Arabizi lexicon consisting of 11.3K positive and 13.3K negative words.We evaluated this lexicon by classifying the sentiment of Arabizi tweets achieving an F1-score of 0.72.We provide a detailed error analysis to present the challenges that impact the sentiment analysis of Arabizi.