• Naveen Kumar G
• Nidhi Kulkarni
• Reshma T
• Netravathi G
• Roopa

Sentiment analysis is the process of computationally identifying and categorizing opinions expressed in text to determine the users’ attitude towards a particular product is positive, negative or neutral. In today’s world, opinions and reviews accessible to us are one of the most critical factors in formulating our views and influencing the success of a brand, product or service. With the advent and growth of social media in the world, stakeholders often take to expressing their opinions on popular social media, namely facebook. While Facebook data is extremely informative, it presents a challenge for analysis because of its humongous and disorganized nature. This paper is a thorough effort to dive into the novel domain of performing sentiment analysis about people’s opinion about Google and apple productions. For performance analysis machine learning approaches such as n-gram technique is used. Hybrid approach is implemented by combining lexicon-based and machine learning algorithms. The result obtained through this approach is feasible to perform sentiment analysis in facebook with high accuracy.

Sentiment, Facebook, N-gram, Lexicon-approach.

"Sentiment Analysis in Facebook using Machine Learning Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.137-144, May-2019, Available :http://www.jetir.org/papers/JETIR1905F21.pdf

"Sentiment Analysis in Facebook using Machine Learning Techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp137-144, May-2019, Available at : http://www.jetir.org/papers/JETIR1905F21.pdf