Python-NLP-Analyze_TextualData_on_Reddit_Comments
wafer110
Data retrieved from Kaggle.com; it is titled “Political Social Media Posts” and consists of 5000 observations with 21 variables. We analyze this data set based on questions that involve natural language processing of one or more variables. Our ultimate goal is to analyze the sentiment of each tweet and see how it varies by different attributes such as audience, message, and political party. In addition, we did Regression and Classification with the label of controversiality to see if it can predict bias.
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6 data points · 2021-07-01 → 2022-11-01How do you feel about this project?
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Question copied to clipboardWhat is the wafer110/Python-NLP-Analyze_TextualData_on_Reddit_Comments GitHub project? Description: "Data retrieved from Kaggle.com; it is titled “Political Social Media Posts” and consists of 5000 observations with 21 variables. We analyze this data set based on questions that involve natural language processing of one or more variables. Our ultimate goal is to analyze the sentiment of each tweet and see how it varies by different attributes such as audience, message, and political party. In addition, we did Regression and Classification with the label of controversiality to see if it can predict bias. ". Written in Jupyter Notebook. Explain what it does, its main use cases, key features, and who would benefit from using it.
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