Due to evolution in every sector around us, a large amount of information is generated at every moment. In recent years, many microblogging platforms have become the primary place for the public to express their mood. So the sentiment analysis data collected from websites, reviews, and feedback can be used in many areas such as in marketing or product analysis or competitive research for future development. So, sentiment analysis is one of the booming domains, a study of analyzing people’s reviews, suggestions, feedback from the text format and checking if the data shows positive, negative, or neutral emotion. Applications of sentiment analysis are endless and are applicable in every social domain. We can automatically assess the tone of internet interactions using natural language processing and machine learning methods. Sentiment analysis can be performed with the help of various techniques, depending on how much data needs to be examined and how precise the model needs to be. This manuscript is a comprehensive article that includes all the essential topics related to sentiment analysis, such as its applications, challenges faced and various algorithms.