Aspect-based sentiment analysis methods in recent years

Aspect-based sentiment analysis methods in recent years

Sentiment Analysis (SA) is the computational treatment of opinions, sentiments and subjectivity of text. Aspect-based Sentiment Analysis (ABSA) is a specific SA that aims to extract most important aspects of an entity and predict the polarity of each aspect from the text. A review of the recent stat...

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Main Authors: Madhoushi, Zohreh, Abdul Razak Hamdan, Suhaila Zainudin
Format: Article
Language:English
Published: Penerbit Universiti Kebangsaan Malaysia 2019
Online Access:http://journalarticle.ukm.my/14153/
http://journalarticle.ukm.my/14153/
http://journalarticle.ukm.my/14153/1/28204-107928-1-PB.pdf
id ukm-14153
recordtype eprints
spelling ukm-141532020-02-07T11:08:23Z http://journalarticle.ukm.my/14153/ Aspect-based sentiment analysis methods in recent years Madhoushi, Zohreh Abdul Razak Hamdan, Suhaila Zainudin, Sentiment Analysis (SA) is the computational treatment of opinions, sentiments and subjectivity of text. Aspect-based Sentiment Analysis (ABSA) is a specific SA that aims to extract most important aspects of an entity and predict the polarity of each aspect from the text. A review of the recent state-of-the-art in ABSA, shows the remarkable growing in finding both aspect, and the corresponding sentiment. Current methods are categorized based on their proposed algorithms and models. For each discussed study, aspect extraction method and sentiment prediction method, the dataset, domain and the reported performance is included. The main goal of this work is to review ABSA techniques with brief details. The main contributions of this paper consist of the refined categorizations of a great number of recent articles, comparing them and the illustration of the recent trend of research in the ABSA. Penerbit Universiti Kebangsaan Malaysia 2019-06 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/14153/1/28204-107928-1-PB.pdf Madhoushi, Zohreh and Abdul Razak Hamdan, and Suhaila Zainudin, (2019) Aspect-based sentiment analysis methods in recent years. Asia-Pacific Journal of Information Technology and Multimedia, 8 (1). pp. 79-96. ISSN 2289-2192 http://ejournals.ukm.my/apjitm/issue/view/1179
repository_type Digital Repository
institution_category Local University
institution Universiti Kebangasaan Malaysia
building UKM Institutional Repository
collection Online Access
language English
description Sentiment Analysis (SA) is the computational treatment of opinions, sentiments and subjectivity of text. Aspect-based Sentiment Analysis (ABSA) is a specific SA that aims to extract most important aspects of an entity and predict the polarity of each aspect from the text. A review of the recent state-of-the-art in ABSA, shows the remarkable growing in finding both aspect, and the corresponding sentiment. Current methods are categorized based on their proposed algorithms and models. For each discussed study, aspect extraction method and sentiment prediction method, the dataset, domain and the reported performance is included. The main goal of this work is to review ABSA techniques with brief details. The main contributions of this paper consist of the refined categorizations of a great number of recent articles, comparing them and the illustration of the recent trend of research in the ABSA.
format Article
author Madhoushi, Zohreh
Abdul Razak Hamdan,
Suhaila Zainudin,
spellingShingle Madhoushi, Zohreh
Abdul Razak Hamdan,
Suhaila Zainudin,
Aspect-based sentiment analysis methods in recent years
author_facet Madhoushi, Zohreh
Abdul Razak Hamdan,
Suhaila Zainudin,
author_sort Madhoushi, Zohreh
title Aspect-based sentiment analysis methods in recent years
title_short Aspect-based sentiment analysis methods in recent years
title_full Aspect-based sentiment analysis methods in recent years
title_fullStr Aspect-based sentiment analysis methods in recent years
title_full_unstemmed Aspect-based sentiment analysis methods in recent years
title_sort aspect-based sentiment analysis methods in recent years
publisher Penerbit Universiti Kebangsaan Malaysia
publishDate 2019
url http://journalarticle.ukm.my/14153/
http://journalarticle.ukm.my/14153/
http://journalarticle.ukm.my/14153/1/28204-107928-1-PB.pdf
first_indexed 2023-09-18T20:06:27Z
last_indexed 2023-09-18T20:06:27Z
_version_ 1777407191141056512

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