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SentiHealth: creating health-related sentiment lexicon using hybrid approach

The exponential increase in the health-related online reviews has played a pivotal role in the development of sentiment analysis systems for extracting and analyzing user-generated health reviews about a drug or medication. The existing general purpose opinion lexicons, such as SentiWordNet has a li...

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Autores principales: Asghar, Muhammad Zubair, Ahmad, Shakeel, Qasim, Maria, Zahra, Syeda Rabail, Kundi, Fazal Masud
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4954801/
https://www.ncbi.nlm.nih.gov/pubmed/27504237
http://dx.doi.org/10.1186/s40064-016-2809-x
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author Asghar, Muhammad Zubair
Ahmad, Shakeel
Qasim, Maria
Zahra, Syeda Rabail
Kundi, Fazal Masud
author_facet Asghar, Muhammad Zubair
Ahmad, Shakeel
Qasim, Maria
Zahra, Syeda Rabail
Kundi, Fazal Masud
author_sort Asghar, Muhammad Zubair
collection PubMed
description The exponential increase in the health-related online reviews has played a pivotal role in the development of sentiment analysis systems for extracting and analyzing user-generated health reviews about a drug or medication. The existing general purpose opinion lexicons, such as SentiWordNet has a limited coverage of health-related terms, creating problems for the development of health-based sentiment analysis applications. In this work, we present a hybrid approach to create health-related domain specific lexicon for the efficient classification and scoring of health-related users’ sentiments. The proposed approach is based on the bootstrapping modal, a dataset of health reviews, and corpus-based sentiment detection and scoring. In each of the iteration, vocabulary of the lexicon is updated automatically from an initial seed cache, irrelevant words are filtered, words are declared as medical or non-medical entries, and finally sentiment class and score is assigned to each of the word. The results obtained demonstrate the efficacy of the proposed technique.
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spelling pubmed-49548012016-08-08 SentiHealth: creating health-related sentiment lexicon using hybrid approach Asghar, Muhammad Zubair Ahmad, Shakeel Qasim, Maria Zahra, Syeda Rabail Kundi, Fazal Masud Springerplus Research The exponential increase in the health-related online reviews has played a pivotal role in the development of sentiment analysis systems for extracting and analyzing user-generated health reviews about a drug or medication. The existing general purpose opinion lexicons, such as SentiWordNet has a limited coverage of health-related terms, creating problems for the development of health-based sentiment analysis applications. In this work, we present a hybrid approach to create health-related domain specific lexicon for the efficient classification and scoring of health-related users’ sentiments. The proposed approach is based on the bootstrapping modal, a dataset of health reviews, and corpus-based sentiment detection and scoring. In each of the iteration, vocabulary of the lexicon is updated automatically from an initial seed cache, irrelevant words are filtered, words are declared as medical or non-medical entries, and finally sentiment class and score is assigned to each of the word. The results obtained demonstrate the efficacy of the proposed technique. Springer International Publishing 2016-07-20 /pmc/articles/PMC4954801/ /pubmed/27504237 http://dx.doi.org/10.1186/s40064-016-2809-x Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Research
Asghar, Muhammad Zubair
Ahmad, Shakeel
Qasim, Maria
Zahra, Syeda Rabail
Kundi, Fazal Masud
SentiHealth: creating health-related sentiment lexicon using hybrid approach
title SentiHealth: creating health-related sentiment lexicon using hybrid approach
title_full SentiHealth: creating health-related sentiment lexicon using hybrid approach
title_fullStr SentiHealth: creating health-related sentiment lexicon using hybrid approach
title_full_unstemmed SentiHealth: creating health-related sentiment lexicon using hybrid approach
title_short SentiHealth: creating health-related sentiment lexicon using hybrid approach
title_sort sentihealth: creating health-related sentiment lexicon using hybrid approach
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4954801/
https://www.ncbi.nlm.nih.gov/pubmed/27504237
http://dx.doi.org/10.1186/s40064-016-2809-x
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