Sentiment analysis is a burgeoning domain within the field of natural language processing, which entails identifying and obtaining the viewpoint conveyed in a certain text. Sentiment analysis can be used to save time reading thousands of reviews of a product or a service, and can help consumers make faster and accurate decisions. Sentiment analysis can also be leveraged by manufacturers to understand the public’s opinion over their product which can be used to improve services and increase consumer satisfaction and bolster sales. This study offers a thorough analysis of the opinion mining techniques now in use, including Support Vector Machine, Naive Bayes, Decision Trees, and Unsupervised Algorithms and highlights their advantages and disadvantages. The paper also mentions the application of sentiment analysis in the cybersecurity field to study people's attitudes and behaviours during cybercrimes. The findings of this paper aim to highlight present work performed to discern the emotional tone from textual matter.