Opinion mining analysis and classification of social media through machine learning techniques
Sukhendra Singh, Santosh Kumar · 2025
Amongst modern online users, blogging has emerged as one of the most widely used means of interaction. Every day, countless tweets are posted on well-known social media websites including LinkedIn, Twitter, Facebook, The tumbler, and Stumble upon. Thousands of individuals utilize tiny websites every single day to exchange thoughts on a wide range of subjects. Users are limited to 140 characters on major online blogging sites like Facebook and LinkedIn, which helps users be comprehensible and audible. It provides an important resource for sentiment assessment and religion mining as a result. This research aims to develop a functioning categorization system that can precisely and automatically interpret the significance of an anonymously tweet. The suggested exercise uses an extraction scalar or a pattern computing network to analyze the sentiments expressed in comments regarding something through the online retailer&s;s repository.