Twitter Sentiment Analysis

Dodd, John (2014) Twitter Sentiment Analysis. Diploma thesis, Dublin, National College of Ireland.

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Over the past decade humans have experienced exponential growth in the use of online resources, in particular social media and microblogging websites such as Twitter. Many companies and organisations have identified these resources as a rich mine of marketing knowledge. This project focuses implementing machine learning algorithms to extract an audience’s sentiment relating to a popular television program. A major focus of this study was on comparing different machine learning algorithms for the task of sentiment classification. The major findings were that out of the classification algorithms evaluated it was found that the Random forest classifier provide the highest classification accuracy for this domain. From the evaluation of this study it can be concluded that the proposed machine learning and natural language processing techniques are an effective and practical methods for sentiment analysis.

Item Type: Thesis (Diploma)
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
Divisions: School of Computing > Higher Diploma in Science in Data Analytics
Date Deposited: 15 Dec 2014 13:11
Last Modified: 15 Dec 2014 13:11

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