Today the evolution of technology and fair access to the internet in countries such as India, public opinions over social media, expression of sentiment on products and services are fast and furious in present days. These opinions have value for companies to materialize profits and understand the market for their future strategic decisions. Present technology adoption energized by the healthy growth in big data framework, caused applications based on Sentiment Analysis (SA) in big data to become common for businesses. But there is wide gap and scope for SA application in big data. This paper discusses various Sentiment analysis approaches and algorithms, including sentiment polarity detection, SA features (explicit and implicit), sentiment classification techniques, applications of SA. Future opportunities and challenges of sentiment analysis is explored. Scalable, automated, accurate, sophisticated sentiment analysis is a much sought-after technology that almost no one has truly nailed yet.

Sentiment Analysis Approaches, tools, techniques, machine Learning, opportunities, and challenges, supervised learning and unsupervised learning

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