Sentimental Analysis of customer review
Author(s):
Aaditya Prakash Pillai, DR.S.P. CHAUHAN
Keywords:
Aspect-based, sentiment analysis, Machine Learning, Natural Language Processing, Streamlit Web application, Support Vector Machine
Abstract
Businesses all over the world are nowadays moving to online platforms. This promises the customer the choice to receive the product at their residence (home-delivery), browse through latest offers and new offers from the comfort of their home. The customer not only receives a service but can also give feedback to the company. These are called customer feedbacks. Customers nowadays look up customer feedback and ratings that the service or product receives before they decide on a purchasing decision. Customer reviews can seriously affect the performance of a company. The final verdict about a company’s overall quality of service or product is influenced by customer feedback or reviews. Using sentiment analysis, customer feedback can be classified as negative, positive or neutral comments. Sentiment analysis is the computational study of people's opinions, sentiments, emotions and attitudes, it is also known as opinion mining. The aim of the paper is to present the existing approaches applied for sentiment analysis using Machine learning and natural Language Processing technique in a service environment and to investigate the accuracy rates of these algorithms and an app will be developed to help the end user, i.e. the company to receive a very good idea about the customer sentiment about their product and/ or service.
Article Details
Unique Paper ID: 154930

Publication Volume & Issue: Volume 8, Issue 12

Page(s): 772 - 779
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