In the arena of information-gathering, the importance lies in getting to know “what other people think?” The explosion of opinion rich contents sourced from personal web blogs and review sites generates vast research prospects, that to identify and understand people’s opinion based on the information gathered over a product or service. Opinion Mining (OM) is a key field under text mining, helps an organisation to understand consumer attitude, to handle customer relationship, to manage product positioning and branding and in market research. This paper presents an investigative study of the performance of various feature extraction methods and classification algorithms for opinion mining. For the evaluation, opinion datasets about camera product are sourced from amazon website and evaluated. Information Gain based feature selection algorithm is used to extract the features and k-NN Boosting algorithm is used for opinion classification. © 2019, Science and Engineering Research Support Society. All rights reserved.