Sentiment analysis, also known as opinion mining, is a branch or field of study within Natural Language Processing (NLP) that analyzes and tries to figure out peoples’ opinions, sentiments, attitudes, and emotions expressed in written text. The main goal of sentiment analysis is to examine the hidden emotional tone or attitude behind the piece of text and then classify it as either positive, negative, or neutral.
Sentiment analysis could be essential in understanding market sentiments in financial markets. It refers to the collection of attitudes and psychology of investors towards the financial market. Through sentiment analysis, people can understand how people’s feelings towards certain assets or market conditions influence stock prices and trading decisions. It utilizes techniques from natural language processing and machine learning to analyze and classify text based on its emotional content automatically. It can helps in managing brand reputation, understanding customer reviews, making informed market decisions , evaluating marketing campaigns, and analyzing financial sentiments to predict market trends.
Even the significance of sentiment analysis in financial markets, there still remains a gap in understanding how sentiment analysis of news titles directly impacts stock price movements in specific markets like Malaysia.
- What is the impact of sentiment analysis of news titles on stock price movements in the financial market of Malaysia?
- Reliability of sentiment values extracted from news headlines in predicting short-term and long-term stock price changes in Malaysia?
- Correlation or any relationships between the sentiment polarity of news titles and the volatility of stock prices in different industry sectors in Malaysia?
- To investigate the effectiveness of sentiment analysis of news titles in predicting weekly or monthly stock price movements in the Malaysian market.
- To examine the accuracy and reliability of sentiment values extracted from news headlines in forecasting weekly and monthly stock price trends in Malaysia.
- To analyze the relationship between sentiment polarity of news titles and the fluctuation of stock prices across various industry sectors in the Malaysian market.
This study will mainly focuses on sentiment analysis of news titles and its impact on stock prices within the Malaysia's financial market, providing a targeted analysis of the applicability and reliability of sentiment analysis in this unique market setting.
The research aims to bridge and reduce existing gaps by exploring the practical implications of sentiment analysis in financial decision-making and offering valuable insights for investors and stakeholders operating in Malaysia's stock market.
This thesis will be structured to delve into parts such as methodology, data analysis, results, and conclusions derived from the research on sentiment analysis of news titles and stock price movements in Malaysia.
This research will address the gap in knowledge regarding the relationship between sentiment analysis of news titles and stock prices in Malaysia, offering practical implications and contributing to advancements in data-driven financial predictions.
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