Classifying whether twitter author spreads hate using supervised learning

Online Setup

https://srinath-m.shinyapps.io/shinyHost

Process Notebook

https://mannam95.github.io/DataScienceR_Project/

Project screencast

https://www.youtube.com/watch?v=_cLzOaIdFXE

Offline Version

These instructions will get you a copy of this project running on your local machine for development and testing purposes

Prerequisites

1. Access to the Twitter Dataset Link
2. R (>=4.0.0)
3. RStudio (>=1.4)
4. on Windows: Rtools

Installing

• Clone the repository or download and unzip it.
• Make sure that all the files are present in following folder and in the following similar structure.

DataScienceR(Parent Folder)
    code_Base  
            preprocessFiles
              read_data.R
              Text_preprocessing.R
            feature_Extraction
            exploratory_data_analysis
            models
    datasets  
            dataset_original
            dataset_working
    Plots
    process_Notebook
    project_Proposal
    README.md

Further Instructions:

• Run the setup_Libraries.R file mentioned in the code_Base folder for installing all the packages.
• In order to be able to view only the report created by us, you can navigate to "process_Notebook" folder and run the "Process_notebook_dwr.Rmd" file to generate "Process_notebook_dwr.html" and open this html file in any browser(Chrome etc.) for viewing the report.
• Change the directory paths in all .R files accordingly.
• First run read_data.R file and Text_preprocessing in "preprocessFiles" folder.R respectively. All the xml files will be converted here.
• Second run the Sentiments_Extract.R and followed by CombineFeatures.R in feature_Extraction folder. All the features will be extracted and combined together
• For data visualization run files in the exploratory data analysis folder.
• Models can be trained in the "models" folder.

Contributors

• Anish Singh
• Priyanka Singh
• Ramanpreet Kaur
• Srinath Mannam