In this thesis, we analyze social media data to perform sentiment analysis and trend prediction. The purpose of the study is to understand the sentiments of users expressed on social media platforms and to predict future trends based on this analysis.

Chapter One introduces the topic and discusses the significance of the study in understanding public opinions and behaviors. The objectives of the study and the hypothesis are also outlined, along with the limitations of the study.

Chapter Two provides a comprehensive review of the existing literature on sentiment analysis and trend prediction using social media data. This chapter also discusses the different methodologies and techniques used in previous studies.

Chapter Three describes the research methodology used in this study, including data collection, data preprocessing, sentiment analysis techniques, and trend prediction models. The chapter also discusses the tools and software used for analysis.

Chapter Four presents the findings of the study and discusses the results of the sentiment analysis and trend prediction. It also includes a discussion of the implications of the findings and their potential impact on various industries.

Chapter Five concludes the thesis with a summary of the findings, recommendations for future research, and a final conclusion on the study.

In summary, this thesis aims to provide valuable insights into sentiment analysis and trend prediction using social media data, which can be beneficial for businesses, marketers, and policymakers in understanding public sentiment and predicting future trends.

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