Skip to content

A project on analysing extracted tweets - (Scraped using Twint)

Notifications You must be signed in to change notification settings

Menon-R/Tweet_Analysis

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

12 Commits
 
 
 
 
 
 
 
 

Repository files navigation

Tweet Analysis

A project on analysing extracted tweets - (Scraped using Twint). For this project I chose to extract tweets about the supermarket gaint Coles during the period of March -2020, when Australia was at it's peak on COVID - 19 cases and when the supermarket shelves were empty due to high demand of products as people feared a lockdown.

Prerequisites

These are the things you would need for executing this project.

Python installed on your machine (or) use Google Colab.

Python Libraries used in this project

A list of libraries to install for this project.

Twint - An advanced twitter scraping package
nest_asyncio - Module to patch asyncio to allow nested use of asyncio.run
pyLDAvis -  To extract info. from a fitted LDA topic model to generate an interactive web-based visualization
Pandas - For data analysis and manipulation
Numpy - Array processing package in python
Seaborn - data visualization library based on matplotlib
Matplotlib - library to write 2-dimensional graphs and plots
Textblob - Python NLP libraries – for textual data processing
Logging - logging system as a part of its standard library
Gensim - a python natural library processing library
Tempfile - module to create temporary files and directories
Scikit-learn - an efficient predective analysis tool and also used for machine learning
NLTK - Natural language processing toolkit in python 

Releases

No releases published

Packages

No packages published