Leveraging Data Mining Tools and Techniques to Effectively Execute Sentiment Analysis on Social Media Data
Apoorva Khera · International Journal of Research in Science and Technology · 2021
Lately, online social media has taken a fundamental part in communication and sharing of information. Countless users prefer social media as it is accessible to many individuals with no restrictions to share their understandings and instructive opportunities for growth and concerns through their status. Twitter API is handled to look for the tweets given the geo-area. Understudies' posts on the informal organization give us only worry about concluding the system-specific schooling systems growing experience. Assessing such information in an informal organization is a seriously difficult process. The proposed system will have a work process to mine the information, which incorporates both personal research and massive scope of information mining strategies. In light of the different noticeable subjects, we will classify tweets into various groups. A Naive Bayes classifier will be executed on searched data for personal investigation purposes to comprehend the information better. It involves a multi-name grouping strategy as each mark falls into various classifications, and every one of the characteristics is free. Will take name-based measures to break down the outcomes and distinguish them and the current sentiment analysis procedure.