Work

Arabic Sentiment Analysis by Pretrained Ensemble

Year: 2022

Type: conference-paper

Abstract: This paper presents the 259 team's BERT ensemble designed for the NADI 2022 Subtask 2 (sentiment analysis) (Abdul-Mageed et al., 2022).Twitter Sentiment analysis is one of the language processing (NLP) tasks that provides a method to understand the perception and emotion of the public around specific topics.The most common research approach focuses on obtaining the tweet's sentiment by analyzing its lexical and syntactic features.We used multiple pretrained Arabic-Bert models with a simple average ensembling and then chose the bestperforming ensemble on the training dataset and ran it on the development dataset.This system ranked 3rd in Subtask 2 with a Macro-PN-F1-score of 72.49%.

Source: Arabic Natural Language Processing Workshop (WANLP)

DOI: 10.18653/v1/2022.wanlp-1.47

Author: Abdelrahim Qaddoumi

Institution: New York University

Language: English

Topic: Sentiment Analysis and Opinion Mining

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W4385573313

FWCI:

Cites: 19

Cited by:

Related to: 10