Opinion mining for national security: techniques, domain applications, challenges and research opportunities

Abstract Background Opinion mining, or sentiment analysis, is a field in Natural Language Processing (NLP). It extracts people’s thoughts, including assessments, attitudes, and emotions toward individuals, topics, and events. The task is technically challenging but incredibly useful. With the explos...

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Autores principales:	Noor Afiza Mat Razali, Nur Atiqah Malizan, Nor Asiakin Hasbullah, Muslihah Wook, Norulzahrah Mohd Zainuddin, Khairul Khalil Ishak, Suzaimah Ramli, Sazali Sukardi
Formato:	article
Lenguaje:	EN
Publicado:	SpringerOpen 2021
Materias:	Opinion mining Sentiment analysis National security Machine learning Lexicon-based approach Kansei approach Computer engineering. Computer hardware TK7885-7895 Information technology T58.5-58.64 Electronic computers. Computer science QA75.5-76.95
Acceso en línea:	https://doaj.org/article/ab4d4126be2f460dac41e4f55409f62a
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spelling	oai:doaj.org-article:ab4d4126be2f460dac41e4f55409f62a2021-12-05T12:03:20ZOpinion mining for national security: techniques, domain applications, challenges and research opportunities10.1186/s40537-021-00536-52196-1115https://doaj.org/article/ab4d4126be2f460dac41e4f55409f62a2021-12-01T00:00:00Zhttps://doi.org/10.1186/s40537-021-00536-5https://doaj.org/toc/2196-1115Abstract Background Opinion mining, or sentiment analysis, is a field in Natural Language Processing (NLP). It extracts people’s thoughts, including assessments, attitudes, and emotions toward individuals, topics, and events. The task is technically challenging but incredibly useful. With the explosive growth of the digital platform in cyberspace, such as blogs and social networks, individuals and organisations are increasingly utilising public opinion for their decision-making. In recent years, significant research concerning mining people’s sentiments based on text in cyberspace using opinion mining has been explored. Researchers have applied numerous opinions mining techniques, including machine learning and lexicon-based approach to analyse and classify people’s sentiments based on a text and discuss the existing gap. Thus, it creates a research opportunity for other researchers to investigate and propose improved methods and new domain applications to fill the gap. Methods In this paper, a structured literature review has been done by considering 122 articles to examine all relevant research accomplished in the field of opinion mining application and the suggested Kansei approach to solve the challenges that occur in mining sentiments based on text in cyberspace. Five different platforms database were systematically searched between 2015 and 2021: ACM (Association for Computing Machinery), IEEE (Advancing Technology for Humanity), SCIENCE DIRECT, SpringerLink, and SCOPUS. Results This study analyses various techniques of opinion mining as well as the Kansei approach that will help to enhance techniques in mining people’s sentiment and emotion in cyberspace. Most of the study addressed methods including machine learning, lexicon-based approach, hybrid approach, and Kansei approach in mining the sentiment and emotion based on text. The possible societal impacts of the current opinion mining technique, including machine learning and the Kansei approach, along with major trends and challenges, are highlighted. Conclusion Various applications of opinion mining techniques in mining people’s sentiment and emotion according to the objective of the research, used method, dataset, summarized in this study. This study serves as a theoretical analysis of the opinion mining method complemented by the Kansei approach in classifying people’s sentiments based on text in cyberspace. Kansei approach can measure people’s impressions using artefacts based on senses including sight, feeling and cognition reported precise results for the assessment of human emotion. Therefore, this research suggests that the Kansei approach should be a complementary factor including in the development of a dictionary focusing on emotion in the national security domain. Also, this theoretical analysis will act as a reference to researchers regarding the Kansei approach as one of the techniques to improve hybrid approaches in opinion mining.Noor Afiza Mat RazaliNur Atiqah MalizanNor Asiakin HasbullahMuslihah WookNorulzahrah Mohd ZainuddinKhairul Khalil IshakSuzaimah RamliSazali SukardiSpringerOpenarticleOpinion miningSentiment analysisNational securityMachine learningLexicon-based approachKansei approachComputer engineering. Computer hardwareTK7885-7895Information technologyT58.5-58.64Electronic computers. Computer scienceQA75.5-76.95ENJournal of Big Data, Vol 8, Iss 1, Pp 1-46 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Opinion mining Sentiment analysis National security Machine learning Lexicon-based approach Kansei approach Computer engineering. Computer hardware TK7885-7895 Information technology T58.5-58.64 Electronic computers. Computer science QA75.5-76.95
spellingShingle	Opinion mining Sentiment analysis National security Machine learning Lexicon-based approach Kansei approach Computer engineering. Computer hardware TK7885-7895 Information technology T58.5-58.64 Electronic computers. Computer science QA75.5-76.95 Noor Afiza Mat Razali Nur Atiqah Malizan Nor Asiakin Hasbullah Muslihah Wook Norulzahrah Mohd Zainuddin Khairul Khalil Ishak Suzaimah Ramli Sazali Sukardi Opinion mining for national security: techniques, domain applications, challenges and research opportunities
description	Abstract Background Opinion mining, or sentiment analysis, is a field in Natural Language Processing (NLP). It extracts people’s thoughts, including assessments, attitudes, and emotions toward individuals, topics, and events. The task is technically challenging but incredibly useful. With the explosive growth of the digital platform in cyberspace, such as blogs and social networks, individuals and organisations are increasingly utilising public opinion for their decision-making. In recent years, significant research concerning mining people’s sentiments based on text in cyberspace using opinion mining has been explored. Researchers have applied numerous opinions mining techniques, including machine learning and lexicon-based approach to analyse and classify people’s sentiments based on a text and discuss the existing gap. Thus, it creates a research opportunity for other researchers to investigate and propose improved methods and new domain applications to fill the gap. Methods In this paper, a structured literature review has been done by considering 122 articles to examine all relevant research accomplished in the field of opinion mining application and the suggested Kansei approach to solve the challenges that occur in mining sentiments based on text in cyberspace. Five different platforms database were systematically searched between 2015 and 2021: ACM (Association for Computing Machinery), IEEE (Advancing Technology for Humanity), SCIENCE DIRECT, SpringerLink, and SCOPUS. Results This study analyses various techniques of opinion mining as well as the Kansei approach that will help to enhance techniques in mining people’s sentiment and emotion in cyberspace. Most of the study addressed methods including machine learning, lexicon-based approach, hybrid approach, and Kansei approach in mining the sentiment and emotion based on text. The possible societal impacts of the current opinion mining technique, including machine learning and the Kansei approach, along with major trends and challenges, are highlighted. Conclusion Various applications of opinion mining techniques in mining people’s sentiment and emotion according to the objective of the research, used method, dataset, summarized in this study. This study serves as a theoretical analysis of the opinion mining method complemented by the Kansei approach in classifying people’s sentiments based on text in cyberspace. Kansei approach can measure people’s impressions using artefacts based on senses including sight, feeling and cognition reported precise results for the assessment of human emotion. Therefore, this research suggests that the Kansei approach should be a complementary factor including in the development of a dictionary focusing on emotion in the national security domain. Also, this theoretical analysis will act as a reference to researchers regarding the Kansei approach as one of the techniques to improve hybrid approaches in opinion mining.
format	article
author	Noor Afiza Mat Razali Nur Atiqah Malizan Nor Asiakin Hasbullah Muslihah Wook Norulzahrah Mohd Zainuddin Khairul Khalil Ishak Suzaimah Ramli Sazali Sukardi
author_facet	Noor Afiza Mat Razali Nur Atiqah Malizan Nor Asiakin Hasbullah Muslihah Wook Norulzahrah Mohd Zainuddin Khairul Khalil Ishak Suzaimah Ramli Sazali Sukardi
author_sort	Noor Afiza Mat Razali
title	Opinion mining for national security: techniques, domain applications, challenges and research opportunities
title_short	Opinion mining for national security: techniques, domain applications, challenges and research opportunities
title_full	Opinion mining for national security: techniques, domain applications, challenges and research opportunities
title_fullStr	Opinion mining for national security: techniques, domain applications, challenges and research opportunities
title_full_unstemmed	Opinion mining for national security: techniques, domain applications, challenges and research opportunities
title_sort	opinion mining for national security: techniques, domain applications, challenges and research opportunities
publisher	SpringerOpen
publishDate	2021
url	https://doaj.org/article/ab4d4126be2f460dac41e4f55409f62a
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Opinion mining for national security: techniques, domain applications, challenges and research opportunities

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