The Sellout: Readers Sentiment Analysis of 2016 Man Booker Prize Winner
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Date
2017-08
Journal Title
Journal ISSN
Volume Title
Publisher
INFLIBNET Centre
Abstract
Sentiment analysis also sometimes term as opinion mining refers to the use of natural language
processing, text analysis, computational linguistics, and biometrics to systematically identify, extract,
quantify, and study affective states and subjective information. Sentiment analysis is widely
applied to the voice of the customer materials such as reviews and survey responses, online and
social media, and materials for healthcare applications that range from marketing to customer
service to clinical medicine. This paper mainly focuses on the sentiment analysis of the 2016 Man
Booker prize winner book “The Sellout” in Goodreads website. An opinion is classified as a positive
or negative sentiment, view, attitude, emotion, or appraisal about an entity or an aspect of the entity
from an opinion holder. This is a relevant problem in today’s world as the amount of user generated
text on the web is increasing and sentiment analysis can be used to detect the mood of users on a
forum. The paper examines the positive and negative sentiment polarity of the readers before and
after winning the prize, the most occurred word in the reviews, word frequency and workload.
Description
Keywords
Analysis, Goodreads, Man Booker, R Language, Reviews, Sellout, Sentiment