• Devansh Choudhury
• Varun Sovani
• Mihir Parte
• Priyanka Shahane

Sentiment analysis is the automated extraction of opinions of positive or negative nature from online text. It has gained considerable recognition from testers during this decade. Moreover, the exponential growth of internet users has been advancing rapidly parallel to rising technologies; that laboriously use online review spots, social networks and particular blogs to express their opinions. They harbor positive and negative opinions about people, associations, places, events, and ideas. The tools handed by natural language processing and machine literacy along with other approaches to work with large volumes of text, make it possible to begin rooting sentiments from social media. In this paper we talk over some of the challenges in sentiment extraction, some of the approaches that have been taken to address these challenges and our approach that analyzes sentiments from Twitter social media which not just gives the output beyond the polarity, but uses those polarities in product profiling, trend analysis and soothsaying. Promising results have shown that the approach can be further developed to feed business terrain needs through sentiment analysis in social media.

Sentiment Analysis, Natural Language Processing, Data Mining, Supervised Learning

"Sentiment Analysis on Social Media", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 3, page no.c724-c728, March-2024, Available :http://www.jetir.org/papers/JETIR2403291.pdf

"Sentiment Analysis on Social Media", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 3, page no. ppc724-c728, March-2024, Available at : http://www.jetir.org/papers/JETIR2403291.pdf