Analyzing Customer Sentiment on Social Media for Brand Reputation and Feedback Insights

Shetty, Shresta Sanjeeva (2024) Analyzing Customer Sentiment on Social Media for Brand Reputation and Feedback Insights. Masters thesis, Dublin, National College of Ireland.

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Abstract

This dissertation explores the advancements in sentiment analysis for social media data, focusing on the application of machine learning models, particularly BERT (Bidirectional Encoder Representations from Transformers), for customer feedback analysis on platforms like Twitter. Traditional machine learning methods, such as Decision Trees and Random Forests, have been widely used for sentiment classification, but they often struggle with capturing the complex nuances of language in unstructured text. In contrast, BERT's pre-trained transformer architecture offers a deep understanding of context, significantly improving accuracy in sentiment classification tasks. This study evaluates the performance of BERT against traditional models and investigates the challenges inherent in sentiment analysis, such as class imbalance and the dynamic nature of social media language. By employing resampling techniques and comparing different models, the research highlights the strengths and weaknesses of each approach. The findings demonstrate that BERT outperforms Decision Trees and Random Forests in terms of accuracy and contextual understanding, making it a superior choice for sentiment analysis on social media platforms. This research contributes to the growing body of knowledge on sentiment analysis by showcasing the potential of modern NLP techniques and providing insights into their practical application in customer feedback analysis.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Nolan, Eamon UNSPECIFIED
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science P Language and Literature > P Philology. Linguistics > Computational linguistics. Natural language processing H Social Sciences > HF Commerce > Marketing > Consumer Behaviour Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4150 Computer Network Resources > The Internet > World Wide Web > Websites > Online social networks T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Telecommunications > The Internet > World Wide Web > Websites > Online social networks
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Ciara O'Brien
Date Deposited:	05 Sep 2025 10:37
Last Modified:	05 Sep 2025 10:37
URI:	https://norma.ncirl.ie/id/eprint/8813

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