{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T23:16:10Z","timestamp":1785366970280,"version":"3.55.0"},"reference-count":73,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2021,9,9]],"date-time":"2021-09-09T00:00:00Z","timestamp":1631145600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["BDCC"],"abstract":"<jats:p>Online Social Media (OSM) like Facebook and Twitter has emerged as a powerful tool to express via text people\u2019s 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\u2013computer 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\u20132020 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.<\/jats:p>","DOI":"10.3390\/bdcc5030043","type":"journal-article","created":{"date-parts":[[2021,9,9]],"date-time":"2021-09-09T12:20:37Z","timestamp":1631190037000},"page":"43","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":73,"title":["AI Based Emotion Detection for Textual Big Data: Techniques and Contribution"],"prefix":"10.3390","volume":"5","author":[{"given":"Sheetal","family":"Kusal","sequence":"first","affiliation":[{"name":"Symbiosis Institute of Technology, Symbiosis International (Deemed University), Pune 412115, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4903-1540","authenticated-orcid":false,"given":"Shruti","family":"Patil","sequence":"additional","affiliation":[{"name":"Symbiosis Centre for Applied Artificial Intelligence (SCAAI), Symbiosis Institute of Technology, Symbiosis International (Deemed University), Pune 412115, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2653-3780","authenticated-orcid":false,"given":"Ketan","family":"Kotecha","sequence":"additional","affiliation":[{"name":"Symbiosis Centre for Applied Artificial Intelligence (SCAAI), Symbiosis Institute of Technology, Symbiosis International (Deemed University), Pune 412115, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8508-6066","authenticated-orcid":false,"given":"Rajanikanth","family":"Aluvalu","sequence":"additional","affiliation":[{"name":"Department of CSE, Vardhaman College of Engineering, Hyderabad 500001, India"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3752-7220","authenticated-orcid":false,"given":"Vijayakumar","family":"Varadarajan","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, The University of New South Wales, Sydney, NSW 2052, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,9,9]]},"reference":[{"key":"ref_1","unstructured":"(2021, March 30). 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