Sentiment analysis on Bangladesh cricket team's world cup prospects: a study of Bengali social media comments

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2024-01-25

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Daffodil International University

Abstract

The Bangladesh cricket team has developed a sizable following on social networking sites, where supporters share their thoughts, feelings, and sentiments regarding the team's performance. The purpose of this thesis is to investigate the viability of predicting the performance of the Bangladesh cricket team in the World Cup using sentiment analysis of Bangla comments on social media. In order to do this, I gathered a sizable dataset of comments in Bangla from numerous social media sites, particularly Twitter, Facebook, and Instagram, covering multiple World Cup seasons. I divided these comments into those with favorable, negative, or neutral feelings using natural language processing (NLP) methods and sentiment analysis tools. Then, I employed machine learning algorithms to examine sentiment trends over time and tie them to the effectiveness of the team. According to my research, there is a significant correlation between the attitude exhibited in social media comments and the World Cup performance of the Bangladesh cricket team. I found that a spike in positive sentiment frequently predicts improved team performance, while a spike in negative sentiment frequently accompanies disappointing team performances. In addition, perceptions of certain players, coaches, and team leadership are also important in determining outcomes. In addition, I developed predictive models that anticipate the likelihood that the Bangladesh cricket team would win the World Cup by fusing sentiment analysis with historical data on the team's performance, player statistics, and other pertinent aspects. When used to forecast the team's success, these models showed encouraging accuracy. This study highlights the potential of social media data for forecasting sports results and makes contributions to the growing subject of sports sentiment analysis. By presenting a fresh viewpoint on the impact of social media sentiment in influencing team performance and expectations, it also offers useful insights for cricket authorities, sponsors, and fans. This research concludes by arguing that sentiment analysis of Bangla-language social media comments can be a potent tool for forecasting the success of the Bangladesh cricket team in World Cup competitions.

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Natural Language Processing (NLP), Sports Prediction, Bengali Social Media, Machine Learning

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