• Pooja S. Gadani
• Prof. Gayatri Pandi

With the advance in internet technology blogs and social media generates massive volumes of data. Data relies on various ranges like small text, emojis, images and video etc. Sentiment analysis helps us to evaluate the product or service performance from user-generated contents. The Proposed technique is a combination of Senti-N-Gram technique and Emojis definition from Emojipedia. First, we classify document based on text and emoji content. For sentiment analysis of emojis, we use Emojipedia as our source for definitions. We use a rule-based approach to extract n-gram sentiment score generation. We also propose a sentiment classification methodology by using a ratio based approach based on counts of positive and negative sentences of a document. Then we compare our findings with existing approaches.

Sentiment Analysis, n-gram, Emojipedia, NLP

"An Analysis On Emojis And Text Parsing For Sentiment Analysis", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 12, page no.118-123, December-2018, Available :http://www.jetir.org/papers/JETIR1812216.pdf

"An Analysis On Emojis And Text Parsing For Sentiment Analysis", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 12, page no. pp118-123, December-2018, Available at : http://www.jetir.org/papers/JETIR1812216.pdf