• DR. Akash Saxena
• Vijay Kumar Jangir

Sentiment analysis is a powerful data mining technique used to determine user’s opinion regarding an organization, event, person or product. Micro blogging sites & other social media platforms are gaining massive popularity now days & millions of people comment positively or negatively about various events person in their comments or parts. Micro blogging sites facilitate the public to share & review their opinion& file events in their posts. Sentiment analysis or opinion mining on micro blogging data mining feat. The proposed system is designed to perform sentiment analysis on micro blogging sites using machine learning techniques with variable weighted grading to various definitive words to be positive, negative or neutral. The positive or negativity of words in a tweet is scaled on a factor of 1 to 5. Assigning weight to determined sentiments allow more natural/fuzzy jurisdiction than a simple binary system. Also, a neuro fuzzy inference system is used to compute a grade for specific search keywords which may be on event/entity etc. Thus their presented tool becomes indispensible for anyone who is interested in public sentiment on a event/entity such as NGO’s, social frame works, marketing agencies, manufactures, art industries such as film industries, political parties etc, whoever is affected by public opinion.

Sentiment Analysis, Machine Learning, Opinion Mining, Neuro Fuzzy Grading, Twitter Mining.

"Microblogging Sentiment Analysis Using Machine Learning Weighted Analysis & Automatic Grading Using Neuro-Fuzzy Logic", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 12, page no.610-620, December-2018, Available :http://www.jetir.org/papers/JETIR1812487.pdf

"Microblogging Sentiment Analysis Using Machine Learning Weighted Analysis & Automatic Grading Using Neuro-Fuzzy Logic", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 12, page no. pp610-620, December-2018, Available at : http://www.jetir.org/papers/JETIR1812487.pdf