A comprehensive analysis on diverse algorithms used for sentiment analysis and classification of twitter data

Twitter is a social platform that allows millions of people across the world share their thoughts and ideas, bringing out new connections with large number of audiences. So, whether it’s an event or any latest news people share their views on that with others publicly through this platform. Twitter is being used widely for reporting, marketing, PR Teams, individuals et cetera . Twitter data sentiment analysis has been popular in the research field within the past few years as it helps in getting idea about people’s opinion, their likes and dislikes about certain things, market insights, environmental impact and analysis of customers for m arket product. In this paper a detailed systematic review has been recited about all the past research carried in the field of twit ter data sentiment analysis, various techniques that were used in the process of twitter data mining are analyzed, also the areas where twitters data sentiment analysis has been implemented across many years are being presented along with various challenges that could b e encountered in the future with possible scope of research. This paper is divided into different sections starting with the wo rkflow of twitter data analysis process, section second categorized all the approaches used for twitter data sentiment analysis, third section summarized all the algorithms developed in the past followed by the last section where common findings and gaps are presented .