Welcome to the "Chaos or Clarity" research project repository. This project focuses on sentiment analysis and data compilation for my thesis paper titled "Chaos or Clarity: A Corpus-Assisted Analysis of Top Comments on Jordan Peterson's Controversial YouTube Videos." The full research paper is available on Google Scholar.
In this repository, you will find a collection of Python scripts that are instrumental in the research project. Each script serves a specific role in contributing to the creation of the final dataset for the study. Two primary approaches are used for sentiment analysis:
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VADER Sentiment Analysis: This script utilizes the VADER (Valence Aware Dictionary and sEntiment Reasoner) sentiment analysis tool to gauge the sentiment of textual data.
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TextBlob Sentiment Analysis: The other script employs TextBlob, a natural language processing library, to perform sentiment analysis on the data.
These scripts play a crucial role in extracting sentiment information from textual data, which is a fundamental aspect of the research.
The research project involves various steps beyond sentiment analysis, including:
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Data Pruning: Data preprocessing and cleaning are essential to ensure that the dataset is of high quality and relevant to the research objectives.
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Data Visualization: Data visualization is employed to gain insights and present findings in a clear and comprehensible manner.
If you are interested in contributing to this project or have any related questions, please feel free to reach out to me.
This research project was made possible through the invaluable support of my family, fellow graduate students, and professors at Linnaeus University. Their guidance and feedback significantly contributed to the completion of this project. I extend my heartfelt gratitude to all those who shared their expertise and insights.
This project is licensed under the MIT License - see the LICENSE.md file for details.