Recent advances in the discipline of text based affect recognition

Abstract

Sentiment analysis is a part of natural language processing, along with text mining. Over the years, sentiment analysis has become a key study area for researchers and industries all over the world. The major goal of this review is to overview the papers that have found the sentiment of the data under study over the past few years. Also, the various techniques and methods that have enabled us to solve the problem of sentiment analysis are looked into and put forward briefly. The articles are looked into considering the area of sentiment analysis in which the contributions are made, be it sentiment detection, dataset creation, or transfer learning. This would help the researchers to curate advanced and accurate models and methods for analyzing sentiment. Additionally, they would be given a quick rundown of current developments in this area of research. With this in mind, the literature study is conducted taking into account various applications, various machine learning algorithms, the type of data utilized for analysis purposes, and various performance measurements. Challenges and gaps based on all the contributions studied are summarized. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.