Tobaili, Taha; Fernandez, Miriam; Alani, Harith; Sharafeddine, Sanaa; Hajj, Hazem and Glavas, Goran
(2019).
|
PDF (Accepted Manuscript)
- Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Download (695kB) | Preview |
| Google Scholar: | Look up in Google Scholar |
|---|
Abstract
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.
| Item Type: | Conference or Workshop Item |
|---|---|
| ISBN: | 954-452-056-2, 978-954-452-056-4 |
| Academic Unit/School: | Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi) Faculty of Science, Technology, Engineering and Mathematics (STEM) |
| Item ID: | 66829 |
| Depositing User: | Taha Tobaili |
| Date Deposited: | 20 Sep 2019 15:20 |
| Last Modified: | 02 Oct 2019 13:47 |
| URI: | http://oro.open.ac.uk/id/eprint/66829 |
| Share this page: |     |
Download history for this item
These details should be considered as only a guide to the number of downloads performed manually. Algorithmic methods have been applied in an attempt to remove automated downloads from the displayed statistics but no guarantee can be made as to the accuracy of the figures.
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)