Investigating Deep Learning Word2vec Model for Sentiment Analysis in Arabic and English languages for User’s reviews

Maram Almaghrabi, Girija Chetty

Research output: A Conference proceeding or a Chapter in BookConference contribution

Abstract

In this paper, we explore natural language processing (NLP) methods to perform sentiment analysis or opinion mining. In addition, we show an application on English and Arabic sentiment analysis by implementing sentiment classification for three datasets which are Booking hotel dataset, Food fine Amazon dataset and Arabic movie review dataset. We applied Word2Vec model followed by Random Forest classifier (RF) for Arabic movie dataset. The results show that the Word2Vec model shows highly effective performance in sentiment analysis for English language datasets but it does not work for Arabic language as Arabic language need different mechanism.
Original languageEnglish
Title of host publicationProceedings of the 2019 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages6
ISBN (Electronic)9781728163031
ISBN (Print)9781728163048
DOIs
Publication statusPublished - 9 Dec 2019
EventIEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE 2019) - Melbourne, Melbourne, Australia
Duration: 9 Dec 201911 Dec 2019

Conference

ConferenceIEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE 2019)
Abbreviated titleCSDE 2019
CountryAustralia
CityMelbourne
Period9/12/1911/12/19

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