Sentiment Analysis of Steam Review Datasets using Naive Bayes and Decision Tree Classifier
Zuo, Zhen
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https://hdl.handle.net/2142/100126
Description
Title
Sentiment Analysis of Steam Review Datasets using Naive Bayes and Decision Tree Classifier
Author(s)
Zuo, Zhen
Issue Date
2018-05-09
Keyword(s)
Sentiment Analysis
Naive Bayes
Decision Tree
Feature Selection
Supervised Machine Learning
Text mining
Abstract
Sentiment analysis or opinion mining is one of the
major topics in Natural Language Processing and Text Mining.
This paper will provide a complete process of sentiment analysis
from data gathering and data preparation to final classification
on a user-generated sentimental dataset with Naive Bayes and
Decision Tree classifiers. The dataset used for analysis is the
product reviews from Steam, a digital distribution platform.
The performance of different feature selection models and
classifiers will be compared. The trained classifier can be used
to make prediction for unlabeled reviews and help companies
to increase potential profits in global digital product market.
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