Integrating Sentiment Analysis and Financial Metrics to understand Consumer Behaviour in the Automotive Industry

Lobo, Dale Sanjay (2024) Integrating Sentiment Analysis and Financial Metrics to understand Consumer Behaviour in the Automotive Industry. Masters thesis, Dublin, National College of Ireland.

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Abstract

In this research, the connection between customer emotion as attested to by automotive reviews and the profitability of auto makers is examined through sentiments analysis methods and opposed to deep learning. This work uses NRCLex for sentiment analysis, and also builds two new deep learning models CNN and LSTM to make rating predictions about the customers. Building on the conventional analytics paradigm that sentiment analysis helps to predict a firm’s performance, this study relates customer sentiments to the firm’s performance using sales volume, total revenue, and stock price. The results point to the sales and revenues resulting from the positive impact of sentiment data on overall outcomes. This is particularly useful in the analysis of the automotive industry as it provides insights on which attributes affect car sales rates and in which segments hence helping car makers and dealers target the right aspects of the market. In general, with the help of Random Forest Regressor the resulting model is more stable and efficient. The study also shows how DL models can help improve rating prediction while also noting computational barriers. The research is beneficial to automotive companies that want to capture consumer sentiment in their strategic planning.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Cosgrave, Noel UNSPECIFIED
Subjects:	H Social Sciences > HG Finance Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science H Social Sciences > HF Commerce > Marketing > Consumer Behaviour H Social Sciences > HD Industries. Land use. Labor > Specific Industries > Motor Industry
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Ciara O'Brien
Date Deposited:	03 Sep 2025 11:36
Last Modified:	03 Sep 2025 11:36
URI:	https://norma.ncirl.ie/id/eprint/8738

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