CiiT International Journal of Data Mining and Knowledge Engineering, Vol 8, No 07, July 2016 233 0974-9683/NCRTIT16-042/05/$20/$100 © 2016 CiiT Published by the Coimbatore Institute of Information Technology Abstract---The usage of the internet has improved rapidly in the recent years. Opinion mining intends to examine opinion of a product, services and its attributes. The opinions extracted are in terms of sentiments, subjectivity of text and attitude. Opinion mining is research field of mining textual data from the web. There is a vast increase of textual data in the web. The customers are given an opportunity to write their own opinion on the products they purchase online and use. To categorize these opinions and to find the polarity, opinion mining is used. There are various models, techniques and algorithms proposed for mining these opinions. In this paper, we have examined the latest opinion mining algorithms. These algorithms are evaluated based on their performance. A detailed study has been done which gives an idea of recent algorithms used. Keywords---Opinion Mining- Techniques- Algorithms I. INTRODUCTION PINION mining gathers and classifies opinion regarding the product. Opinion mining is also known as Sentimental Analysis. Opinion mining is useful in number of ways. It assists vendors to assess accomplishment of the newly launched product in the market. It decides which version of the product is well-liked by the customers. It extracts the opinions of users which they provide on a particular product [1-4]. The evolution of opinion mining has been put into five phases. Those five phases were described using the fish-bone diagram. Manuscript received on May 19, 2016, review completed on May 19, 2016 and revised on May 28, 2016. U. Prabu is with the Department of CSE, Shri Krishnaa College of Engineering and Technology, Pondicherry, India. E-Mail: uprabu28@gmail.com P. Balasubramanian is with the Department of CSE, Shri Krishnaa College of Engineering and Technology, Pondicherry, India. E-Mail: pbalasubramanian02@gmail.com M. Sithanandam is with the Department of CSE, Shri Krishnaa College of Engineering and Technology, Pondicherry, India. E-Mail: sithu.cse.235@gmail.com A. Anidha is with the Department of CSE, Shri Krishnaa College of Engineering and Technology, Pondicherry, India. Digital Object Identifier: DMKE072016005. Fig. 1. Five Phases of Opinion Mining Evolution Sentimental analysis is done in three different levels namely: Document level, Sentence level and Phrase level. In document level analysis, objective and subjective sentence classification is much important. Extraneous sentences are removed during processing. The unsupervised and supervised learning methods are used in document level analysis. In sentence level analysis, each sentence's polarity is computed. The positive and negative classes are the two classes of the polarity classification. Phrase level analysis is the identity to opinion mining approaches. The tools used in opinion mining for tracking the polarity are Review Seer tool, Web Fountain, Red opal and Opinion observer. The opinion mining tasks are Subjectivity and Polarity classification, Opinion source identification, Opinion target identification and Opinion summarization. The opinion mining techniques are supervised machine learning, unsupervised machine learning and Case based reasoning. A. Motivation There are quite a few algorithm existing for opinion mining. Each of these algorithms are enclosed by considering certain inputs from various resources. Some algorithm concentrate on the real time opinion whereas some concentrate on the datasets available. So by extracting these features we can obtain the knowledge of opinion mining algorithms. B. Contribution A comprehensive study on opinion mining algorithms is presented in this paper. Opinion are having a major part in today's electronic business world. Without the opinion and reviews the market value of a product can't be determined. The opinion mining algorithms are discussed in depth. To the best of our knowledge, we admit that this a first comprehensive study on recent opinion mining algorithms and their performance evaluation. A Comprehensive Study and Performance Evaluation of Opinion Mining Algorithms U. Prabu, P. Balasubramanian, M. Sithanandam and A. Anidha O