Sentiment Analysis for Youtube

Final Project for Developer Academy Bootcamp

Setup and Installation

Make sure you have Python installed on your machine.

1. Clone this repository or download the ZIP file.
2. Open a terminal/command prompt and navigate to the project directory.
3. Create a virtual environment:
   • Windows: python -m venv venv
   • macOS/Linux: python3 -m venv venv
4. Activate the virtual environment:
   • Windows: venv\Scripts\activate
   • macOS/Linux: source venv/bin/activate
5. Install the requirements: pip install -r requirements.txt

PyTorch with GPU support

It is advised to run pytorch on or gpu, typically using 16GB of memory sentiment analysis takes 15s. CPU takes 20 minutes on a 5900X.

To install PyTorch with GPU support, make sure you have the correct CUDA version installed on your system. Visit the PyTorch installation guide and select the appropriate configuration for your setup. Here is an example command to install PyTorch for CUDA 11.1:

pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu113

Running the App

1. In the terminal/command prompt, ensure you're in the project directory and the virtual environment is activated.
2. Run the app: streamlit run streamlit_app.py

Open your web browser and go to the address shown in the terminal (usually http://localhost:8501) to see the app.

Setting Up API Keys

This application requires access to Google's Youtube API, you need to obtain an API key to use it. Follow these steps to set up your environment:

1. Visit https://developers.google.com/youtube/v3 and follow the instructions to obtain your API key for the Youtube API.

2. Create a file named .env in the root directory of this project.

3. Inside the .env file, add the following line, replacing Your_Api_Key with the key you obtained:

   DEVELOPER_KEY=Your_Api_key

Notes and Tweaks

Youtube search results are current organised by most views to lowest views using 'viewCount'. Adjust to suit your requirement on line 29 of search_term_fetch.py, in the fetch_video_details function.

order='viewCount',

The options available to you are:

date: Resources are ordered by their creation date, with the most recently created resources returned first.
rating: Resources are ordered by their rating, with the highest-rated resources returned first.
relevance: Resources are ordered by their relevance to the search query, with the most relevant resources returned first. This is the default value if no order parameter is specified.
title: Resources are ordered alphabetically by their title.
videoCount: Channels are ordered in descending order of their number of uploaded videos.
viewCount: Resources are ordered by their number of views, with the most viewed resources returned first.