research-article

Sentiment lexicons for health-related opinion mining

Authors:

Lorraine Goeuriot,

Wai Yan Min Kyaing,

Christopher Khoo,

Yin-Leng Theng,

Jung-Jae KimAuthors Info & Claims

IHI '12: Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium

Pages 219 - 226

https://doi.org/10.1145/2110363.2110390

Published: 28 January 2012 Publication History

Abstract

Opinion mining consists in extracting from a text opinions expressed by its author and their polarity. Lexical resources, such as polarized lexicons, are needed for this task. Opinion mining in the medical domain has not been well explored, partly because little credence is given to patients and their opinions (although more and more of them are using social media). We are interested in opinion mining of user-generated content on drugs/medication. We present in this paper the creation of our lexical resources and their adaptation to the medical domain. We first describe the creation of a general lexicon, containing opinion words from the general domain and their polarity. Then we present the creation of a medical opinion lexicon, based on a corpus of drug reviews. We show that some words have a different polarity in the general domain and in the medical one. Some words considered generally as neutral are opinionated in medical texts. We finally evaluate the lexicons and show with a simple algorithm that using our general lexicon gives better results than other well-known ones on our corpus and that adding the domain lexicon improves them as well.

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Cited By

Huisman SKraiss Jde Vos J(2024)Examining a sentiment algorithm on session patient records in an eating disorder treatment setting: a preliminary studyFrontiers in Psychiatry10.3389/fpsyt.2024.127523615Online publication date: 13-Mar-2024
https://doi.org/10.3389/fpsyt.2024.1275236
Dehdarirad TYaghtin M(2024)Gender differences in citation sentimentJournal of Information Science10.1177/0165551522107432750:1(53-65)Online publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1177/01655515221074327
Khine AWettayaprasit WDuangsuwan J(2024)A new word embedding model integrated with medical knowledge for deep learning-based sentiment classificationArtificial Intelligence in Medicine10.1016/j.artmed.2023.102758148:COnline publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1016/j.artmed.2023.102758
Show More Cited By

Index Terms

Sentiment lexicons for health-related opinion mining
1. Applied computing
  1. Life and medical sciences
    1. Health care information systems
2. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing

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Published In

cover image ACM Conferences

IHI '12: Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium

January 2012

914 pages

ISBN:9781450307819

DOI:10.1145/2110363

General Chairs:
Gang Luo
IBM Research, USA
,
Jiming Liu
Hong Kong Baptist University
,
Program Chair:
Christopher C. Yang
Drexel University

Copyright © 2012 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGHIT: ACM Special Interest Group on Health Informatics

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 January 2012

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IHI '12: ACM International Health Informatics Symposium

January 28 - 30, 2012

Florida, Miami, USA

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Cited By

Huisman SKraiss Jde Vos J(2024)Examining a sentiment algorithm on session patient records in an eating disorder treatment setting: a preliminary studyFrontiers in Psychiatry10.3389/fpsyt.2024.127523615Online publication date: 13-Mar-2024
https://doi.org/10.3389/fpsyt.2024.1275236
Dehdarirad TYaghtin M(2024)Gender differences in citation sentimentJournal of Information Science10.1177/0165551522107432750:1(53-65)Online publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1177/01655515221074327
Khine AWettayaprasit WDuangsuwan J(2024)A new word embedding model integrated with medical knowledge for deep learning-based sentiment classificationArtificial Intelligence in Medicine10.1016/j.artmed.2023.102758148:COnline publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1016/j.artmed.2023.102758
Khodaei ABastanfard ASaboohi HAligholizadeh H(2024)A Transfer-Based Deep Learning Model for Persian Emotion ClassificationMultimedia Tools and Applications10.1007/s11042-024-19668-wOnline publication date: 4-Jul-2024
https://doi.org/10.1007/s11042-024-19668-w
Li CFu JLai JSun LZhou CLi WJian BDeng SZhang YGuo ZLiu YZhou YXie SHou MWang RChen QWu Y(2023)Construction of an Emotional Lexicon of Patients With Breast Cancer: Development and Sentiment AnalysisJournal of Medical Internet Research10.2196/4489725(e44897)Online publication date: 12-Sep-2023
https://doi.org/10.2196/44897
Lal CNasir Z(2023)Comparative Analysis of Deep Learning Methods in the Realm of Sentiment Analysis2023 International Multi-disciplinary Conference in Emerging Research Trends (IMCERT)10.1109/IMCERT57083.2023.10075107(1-3)Online publication date: 4-Jan-2023
https://doi.org/10.1109/IMCERT57083.2023.10075107
Khan HFatima N(2023)Analyzing Customer Sentiment in Drug Reviews Using Natural Language Processing2023 7th International Conference on Electronics, Materials Engineering & Nano-Technology (IEMENTech)10.1109/IEMENTech60402.2023.10423529(1-5)Online publication date: 18-Dec-2023
https://doi.org/10.1109/IEMENTech60402.2023.10423529
Alaie AFarooq UBhat WKhurana SSingh P(2023)An Empirical Study on Sentimental Drug Review Analysis Using Lexicon and Machine Learning-Based TechniquesSN Computer Science10.1007/s42979-023-02384-x5:1Online publication date: 6-Dec-2023
https://doi.org/10.1007/s42979-023-02384-x
Denecke KDenecke K(2023)Lexical Resources for Medical Sentiment AnalysisSentiment Analysis in the Medical Domain10.1007/978-3-031-30187-2_7(43-49)Online publication date: 24-Mar-2023
https://doi.org/10.1007/978-3-031-30187-2_7
Joshi DPatwardhan M(2022)Tracing prodromal behaviour by analysing data patterns from social media with ensemble machine learning approachInternational Social Science Journal10.1111/issj.1236873:247(29-50)Online publication date: 30-Nov-2022
https://doi.org/10.1111/issj.12368
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