Journal
ARTIFICIAL INTELLIGENCE REVIEW
Volume 54, Issue 7, Pages 4873-4965Publisher
SPRINGER
DOI: 10.1007/s10462-021-10030-2
Keywords
Social opinion mining; Opinion mining; Social media; Microblogs; Social networks; Social data analysis; Social data; Subjectivity analysis; Sentiment analysis; Emotion analysis; Irony detection; Sarcasm detection; Natural language processing; Artificial intelligence; Systematic review; Survey
Categories
Funding
- ADAPT Centre for Digital Content Technology
- SFI Research Centres Programme [13/RC/2106]
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Social Opinion Mining research focuses on identifying various opinion dimensions in user-generated content across social media platforms, contributing to the evolution of Artificial Intelligence and real-world applications in marketing, politics, and healthcare. The in-depth analysis covers aspects such as social media platforms, techniques, social datasets, tools and technologies, and future research directions.
Social media popularity and importance is on the increase due to people using it for various types of social interaction across multiple channels. This systematic review focuses on the evolving research area of Social Opinion Mining, tasked with the identification of multiple opinion dimensions, such as subjectivity, sentiment polarity, emotion, affect, sarcasm and irony, from user-generated content represented across multiple social media platforms and in various media formats, like text, image, video and audio. Through Social Opinion Mining, natural language can be understood in terms of the different opinion dimensions, as expressed by humans. This contributes towards the evolution of Artificial Intelligence which in turn helps the advancement of several real-world use cases, such as customer service and decision making. A thorough systematic review was carried out on Social Opinion Mining research which totals 485 published studies and spans a period of twelve years between 2007 and 2018. The in-depth analysis focuses on the social media platforms, techniques, social datasets, language, modality, tools and technologies, and other aspects derived. Social Opinion Mining can be utilised in many application areas, ranging from marketing, advertising and sales for product/service management, and in multiple domains and industries, such as politics, technology, finance, healthcare, sports and government. The latest developments in Social Opinion Mining beyond 2018 are also presented together with future research directions, with the aim of leaving a wider academic and societal impact in several real-world applications.
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