Tweet Sentiment Analysis V2

Based on labeled-tweet-generator by @rhnvrm.

Instructions

Twitter API

You need to go here and sign in with your Twitter account, create an app to get the Twitter API keys we will be using in this project. Now, create a new file called .env.json in the project folder and copy-paste the following contents:

{
    "consumer_key": "<YOUR_CONSUMER_KEY>",
    "consumer_secret": "<YOUR_CONSUMER_SECRET_KEY>",
    "access_token": "<YOUR_ACCESS_TOKEN>",
    "access_token_secret": "<YOUR_ACCESS_TOKEN_SECRET>"
}

Replace the placeholder values with the keys you obtained from Twitter and save the file.

Main Steps

1. Get Python 3.x installed. I'm using 3.6. I suggest to install Python using the Anaconda distribution available here.
2. (Optional) Create a new virtual environment using conda create and activate that environment.
3. Clone this repo to your computer and change into that directory in your terminal. Note: If you followed (2), make sure you activate the environment before proceeding any further.
4. Do pip install -r requirements.txt. This will take a while to download the dependencies for running this project.
5. Since we're using NLTK, you need to download the NTLK datasets. For that, open REPL by typing in python and hitting enter. Enter the following:

   >> import nltk
   >> nltk.download()
   

6. The NLTK client app will appear. From here, download all the datasets (This will take a while as some of the datasets are in GBs. You can just download a part of the datasets but then, NLTK might not work well).
7. Follow the instructions above for generating Twitter API keys and to create .env.json.
8. Now, from your terminal, type python app.py to start the server. Open a browser and go to http://localhost:5000 to see the visualization.

Authors

1. Sangeeth Sudheer
2. Amol Suraj Mishra
3. Aadithyavarma

Screenshots