• Ms. Varsha S. Nagpurkar
• Jayashri Mittal

Abstract : Social medias such as face-book, Google +, Instagram, Myspace, and Twitter are the collective of online communications channels dedicated to community-based input, interaction, content-sharing and collaboration, which helps people to share the public opinions about the products, political analysis and movie reviews, etc. In this paper, public opinion is created to make an attempt on DeMonetization (DeMon) policy in India. Initially, the DeMon twitter data were collected from November 9 to December 3, which was considered for experimental analysis. Usually, the noises such as URLs, positive and negative emoji, stop words were reduced from raw tweets in the pre-processing stage. The twitter sentiment analysis (TSA) was done by Possibilistic fuzzy c-means (PFCM) approach to pre-processed twitter data. The optimal clustering heads from the sentimental contents were found out by the proposed clustering method for acquired twitter data. The PFCM obtained the three types of results such as positive, negative and neutral to validate the TSA on DeMon. The experimental results showed that PFCM approach improved the accuracy in TSA upto 3-20% when compared with existing methods namely Bernoulli naive Bayes, multinomial naive Bayes, Support Vector Machine (SVM), decision tree and Linear Discriminant Analysis (LDA).

Demonetization, machine learning, possibilistic fuzzy c-means, twitter sentiment analysis.

"Twitter sentiment analysis on demonetization using possibilistic fuzzy c-means approach", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.103-111, May-2019, Available :http://www.jetir.org/papers/JETIR1905E15.pdf

"Twitter sentiment analysis on demonetization using possibilistic fuzzy c-means approach", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp103-111, May-2019, Available at : http://www.jetir.org/papers/JETIR1905E15.pdf