Abstract
In today’s society, sentiment analysis has gained due importance as it provides useful information about products that are used by variety of users. It gives a sneak peek of users’ reactions towards the products that are available in the market at an early stage. It thus intimates users’ perception and charts out a path that is beneficial for the market to grow as a whole. Although a lot of research is done to exploit the product based sentiment analysis but due to increase demand of the detailed components based products and their associated features, a novel method is desired to meet these criteria. So far, no such method is explored that analyses the product’s components and their features simultaneously, on the basis of sentiments of the users. This paper proposes an improvised Feature Based Algorithm (FBA) for the sentiment analysis of product reviews while formulating a tree structure of product, components, and associated features. In addition, evaluation of double negative sentences, detecting questions and emotions from the review sentences are measured which increases efficiency of the FBA method. The comparison of product’s components reviews is done with other existing algorithmsTF, TF-IDF and Naive Bayes to demonstrate that the proposed FBA is coherent and auspicious.
Highlights
It is quite visible to all of us that social media is growing at an explosive rate
It is observed that sentimental analysis plays a vital role in decision making for the users about the choice of a product
Indices of the product components are obtained from the pre-defined tree structure
Summary
It is quite visible to all of us that social media is growing at an explosive rate. Everything is just a click away from the users. The fact is that there is a huge reservoir of information available on the web which makes it very difficult to process and analyse according to users’ needs. The sentiments can be defined as ones feelings or thoughts that are expressed in words on the web, in the form of opinions. It is essential to do proper classification which expresses the feature specific details of a product, and is beneficial for both- seller and buyer, to determine the best product that is available in the market according to users’ feedback in the form of their opinions. An improvised Feature Based Algorithm (FBA) for sentiment analysis of product reviews is proposed while using the polarity of the components of a product.
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