IRWA

Students

Name	Email	UPF uNum
Clara Pena	clara.pena01@estudiant.upf.edu	u186416
Yuyan Wang	yuyan.wang01@estudiant.upf.edu	u199907

How to Run the Notebook

0. The recommended approach would be to create a Python3 virtual environment and activate it; however it is not essentially needed. Skip to next step if you don't want to use a venv.

   $ python -m venv <nameVenv>
   $ source <youPathToVenvActivate>
   

1. Installing the necessary packages. We are providing the requirements.txt file.

   $ pip install -r requirements.txt
   

2. Use the corresponding Python3 as the Jupyter Notebook Kernel

3. Locate yourself inside the project part folder that you would like to execute. E.g. for part 1 you should cd the folder named Part1

   $ cd <projectPartXFolder>
   

4. The structure of the working directory for each part should look like:

   • Part 1:

     Part1/
     ├── data/
     │   ├── evaluation_gt.csv
     │   ├── farmers-protest-tweets.json
     │   └── tweet_document_ids_map.csv
     ├── Fonts/
     │   ├── NotoSans.ttf
     │   ├── NotoSansDevanagari.ttf
     │   └── NotoSansGurmukhi.ttf
     ├── project1.ipynb
     └── processed_data.csv  # This will be generated after running the script
     

   • Part 2:

     Part2/
     ├── data/
     │   ├── processed_data.csv  # This would be the one generated from Part 1
     │   ├── evaluation_gt.csv
     │   └── personalized_evaluation_gt.csv
     └── project2.ipynb
     

   • Part 3:

     Part3/
     ├── data/
     │   ├── processed_data.csv  # This would be the one generated from Part 1
     ├── visualizations/ # All png will be generated after running the notebook
     │   ├── bjpparti.png 
     │   ├── humanrightviolat.png 
     │   ├── indiaprotest.png 
     │   ├── modishame.png 
     │   └── supportfarmer.png 
     └── project3.ipynb
     

   • Part 4:

     Part4/
     ├── flask_sessions/              # Session storage directory (we recommend put this in .gitignore)
     ├── myapp/
     │   ├── core/
     │   │   └── utils.py             # Core utility functions
     │   ├── search/
     │   │   ├── load_corpus.py       # Script to load the corpus
     │   │   ├── objects.py           # Data model definitions
     │   │   └── search_engine.py     # Search engine implementation
     ├── static/
     │   ├── styles/
     │   │   ├── bootstrap.min.css    # Bootstrap styles
     │   │   ├── bootstrap.min.css.map # Bootstrap map file
     │   │   └── custom.css           # Custom styles for the application
     │   ├── farmers-protest-tweets.json  # Dataset used in the search engine
     │   │                                # IMPORTANT: this file is not uploaded in github, you should have it locally; 
     │   ├── logo.png                 # Project logo
     │   └── processed_data.csv       # Preprocessed data file
     ├── templates/
     │   ├── all_sessions.html        # HTML for all sessions analytics
     │   ├── analytics.html           # HTML for general analytics
     │   ├── base.html                # Base layout for templates
     │   ├── doc_details.html         # Document details page
     │   ├── index.html               # Homepage template
     │   └── results.html             # Search results page
     ├── README.md                    # This README file
     └── web_app.py                   # Main Flask application