Abstract
Online Social Media (OSM) like Facebook and Twitter has emerged as a powerful tool to express via text people’s opinions and feelings about the current surrounding events. Understanding the emotions at the fine-grained level of these expressed thoughts is important for system improvement. Such crucial insights cannot be completely obtained by doing AI-based big data sentiment analysis; hence, text-based emotion detection using AI in social media big data has become an upcoming area of Natural Language Processing research. It can be used in various fields such as understanding expressed emotions, human–computer interaction, data mining, online education, recommendation systems, and psychology. Even though the research work is ongoing in this domain, it still lacks a formal study that can give a qualitative (techniques used) and quantitative (contributions) literature overview. This study has considered 827 Scopus and 83 Web of Science research papers from the years 2005–2020 for the analysis. The qualitative review represents different emotion models, datasets, algorithms, and application domains of text-based emotion detection. The quantitative bibliometric review of contributions presents research details such as publications, volume, co-authorship networks, citation analysis, and demographic research distribution. In the end, challenges and probable solutions are showcased, which can provide future research directions in this area.
Highlights
Out of 7.8 billion people worldwide, 50.64% of the population uses social networks, irrespective of their age [1]
Elsevier’s Scopus and Clarivate Analytics’ Web of Science (WoS) database platforms were used for retrieving the documents for the analysis
On the above-specified query search, 1011 research publications were retrieved from Scopus, and 324 research publications were retrieved from Web of Science
Summary
Out of 7.8 billion people worldwide, 50.64% of the population uses social networks, irrespective of their age [1]. Popular social networking sites like Facebook, Instagram, YouTube, WhatsApp, FB messenger, Twitter, and Reddit are used by this population. Twitter, Instagram, and Reddit are very widely used microblogging sites where people make short, frequent posts from these social networks. Online Social Media (OSM) platforms provide the opportunity to express, communicate, and share people’s opinions, thoughts, views, and perspectives—on local and international issues, matters, and topics—through text, image, audio, and video posts. Posts on social media are public and abundant in emotions. Analyzing and studying these posts from social media may indicate emotional states and the reasons behind those emotions. The massive volume of this data makes this analysis very difficult
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