• K. Varshaa
• P. Edith Linda
• R. Kiruthika

Nowadays, businesses are using social media to connect with customers and get a feel for market trends, which is pretty amazing, don't you think? Social platforms have become a huge part of shaping how people view products and make buying choices. With so many folks sharing their thoughts online, companies can dive into this treasure trove of data to understand how customers feel and how it ties to their purchasing habits. This study is all about blending sentiment analysis of social media with sales forecasting, giving businesses the tools they need to make smarter, more informed choices based on data. Social media analytics are such a fantastic way to understand what customers are feeling, what they like, and how they behave. The idea here is to combine insights from social media sentiment with sales patterns to help organizations predict market trends and make better decisions. Using Natural Language Processing (NLP) and machine learning, this system will dive into social media data to gauge customer sentiment, then connect those sentiment patterns with past sales data to build a really accurate sales forecasting model.

"Integrated Social Media Sentiment Analysis and Sales Forecasting", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 3, page no.f313-f322, March-2025, Available :http://www.jetir.org/papers/JETIR2503567.pdf

"Integrated Social Media Sentiment Analysis and Sales Forecasting", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 3, page no. ppf313-f322, March-2025, Available at : http://www.jetir.org/papers/JETIR2503567.pdf