Date of Award

2017

Publisher

North Dakota State University

Document Type

Master's Paper

Degree Awarded

Master of Science (MS)

Program

Software Engineering

Department

Computer Science

College

Engineering

Faculty Advisor

Nygard, Kendall

Description

Sentiment analysis is the task of finding people’s opinions about specific objects/matters. Ordinary people’s opinions affect the decision-making process. Today, there is a massive explosion of “sentiments” available on social media, e.g. Twitter. Twitter is one of the most popular worldwide social-networking services. Twitter is a widely-used way to get people’s opinion about some topics when you read their posts. In this study, a model was coded in R environment and implemented and tested using a large dataset to estimate people’s opinions concerning specific topics that can be used for implementing better decision in market research. To achieve this goal, a large set of Twitter data along with a reference to a specific business was captured and fed to two models namely, Naïve Bayes and Support Vector Machine (SVM) to classify them. Then, I obtained the result at identifying percentage of positive and negative opinions towards the specific business.

Rights

NDSU Policy 190.6.2

Rights Link

https://www.ndsu.edu/fileadmin/policy/190.pdf

Handle Identifier

https://hdl.handle.net/10365/25984

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