Dimensionality Reduction in Sentiment Analysis Using Colony–Support Vector Machine
Harjeet Kaur1, Prabhjeet Kaur2

1Harjeet Kaur, Department of CSE, Sachdeva Engineering College for Girls, Gharuan,Mohali, India.
2Prabhjeet Kaur, Department of CSE, Sachdeva Engineering College for Girls, Gharuan,Mohali, India.

Manuscript received on 02 June 2019 | Revised Manuscript received on 10 June 2019 | Manuscript published on 30 June 2019 | PP: 2791-2797 | Volume-8 Issue-8, June 2019 | Retrieval Number: H6988068819/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: With the advent of technology in different areas, sentiment analysis is an emerging field with advancement of internet of things. Analyzing the sentiments, views, estimations, conduct and feeling through textual or written format is known as sentiment analysis or opinion mining. Generally, huge amount of data is available on the internet for example the data that is present in blogs, assessment websites, feedback forums and so forth. Internet of things is incentive to these developments. A large amount of information that is available on internet is amorphous and manageable from internal areas in websites, evaluation sites, and review forums. Presently, a number of people prefer online shopping, because there are several sources for buying products; thus making it less time consuming and cost effective. In addition, sentiments, views and feelings of the customers in the reviews and comments can be categorized as positive, negative or neutral; that helps the new customers to make decision about the quality of the product and about the company. In this paper, a unique approach is built on a specific subject by trusting the reviews on social sites. Proposed approach contains a list of the words that is used to design information based training group (positive keyword and negative keyword). In the research work Colony-SVM (Support vector machine) is used for classification of sentiments and KPCA to reduce feature dimensionality. Performance analysis has defined some likely consequences on the existing work when compared to our proposed model. Along with this, feature vector method is implemented using two stages after pre-processing method. In this research, initially data is collected from the social sites like Amazon etc along with extraction of unique features from gathered information then adding it to features vector and value set. In this research work step by step description of reviews and sentiment analysis is performed. This paper also defines a comparative analysis of Machine learning algorithms with accuracy rate, class precision and recall.
Keyword: Sentiment Analysis, Opinion mining Machine learning, Internet of things.
Scope of the Article: Machine Design