International Journal of Electrical and Computer Engineering (IJECE) Vol. 7, No. 5, October 2017, pp. 2818~2822 ISSN: 2088-8708, DOI: 10.11591/ijece.v7i5.pp2818-2822  2818 Journal homepage: http://iaesjournal.com/online/index.php/IJECE Insights to Problems, Research Trend and Progress in Techniques of Sentiment Analysis Kumar P. K. 1 , Nandagopalan S. 2 1 Department of MCA, Post Graduate Studies, VTU, MysoreRegion, Mysuru, India 2 Department of Computer Science & Engineering, Bangalore Institute of Technology, Bangalore, India Article Info ABSTRACT Article history: Received Mar 6, 2017 Revised May 17, 2017 Accepted Aug 11, 2017 The research-based implementations towards Sentiment analyses are about a decade old and have introduced many significant algorithms, techniques, and framework towards enhancing its performance. The applicability of sentiment analysis towards business and the political survey is quite immense. However, we strongly feel that existing progress in research towards Sentiment Analysis is not at par with the demand of massively increasing dynamic data over the pervasive environment. The degree of problems associated with opinion mining over such forms of data has been less addressed, and still, it leaves the certain major scope of research. This paper will brief about existing research trends, some important research implementation in recent times, and exploring some major open issues about sentiment analysis. We believe that this manuscript will give a progress report with the snapshot of effectiveness borne by the research techniques towards sentiment analysis to further assist the upcoming researcher to identify and pave their research work in a perfect direction towards considering research gap. Keywords: Knowledge discovery Natural language processing Text mining Opinion mining Sentiment analysis Copyright © 2017 Institute of Advanced Engineering and Science. All rights reserved. Corresponding Author: Kumar P. K. , Department of MCA, Post Graduate Studies, VTU, Mysore Region, Mysuru, India Email: kumar.pk.krushna@gmail.com 1. INTRODUCTION The process of sentiment analysis can be said to be a form of application that combines applies the concept of text analytics, computational linguistics as well as natural language processing [1]. It is also called as opinion mining and is referred to a method of determining as well as extracting the subjective information about the source materials [2]. The problems associated with this area are also referred to as multi- disciplinary intelligence problems that target to create a communication bridge between computer and human [3]. This field of study can also be said to be using both electronic intelligence as well as human intelligence for the purpose of extracting knowledge as well as categorizing different forms of discrete sentiments [4]. As the numbers of social network applications are increasing, it gave birth to the sentiment analysis. The users are now more interested to share their opinion on the internet using ratings, reviews, and a suggestion with diversified forms of user’s expression. These opinions are used by the stakeholders to understand the user’s requirement as well as flaws/success factor involved in their process management towards product/service design. As nowadays, complete business process is on the verge of automation, so it is quite eminent that there are all the possibilities of noisy data or certain unscrupulous data that could overall reduce the genuine factor about the user reviews or opinion. Sentiment analysis also suffers from the bigger set of problems. The significant problem about it is the usage of very simplified terms to represent express emotions (or sentiment) related to specific service/product. Apart from this, various forms of linguistic-related factors, cultural scales, and dynamic context make the process of sentiment analysis further challenging. It is a