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Twitter Account | Sentimental Analysis

Jupyter Notebook 75.44% Python 8.05% CSS 6.32% HTML 8.63% JavaScript 1.56%
scraping sentiment-analysis toxic-comment-classification twitter

twitter-account-analysis's Introduction

twitter-account-analysis

This is a project to analyze the tweets of a twitter account. It uses BERT to classify the tweets into multiple categories. The categories are as below

collab link - https://colab.research.google.com/drive/1GZP1qv84h6iPXi695NXg3dkraecfsmVn?usp=sharing

Dataset

The types of toxicity are:

  • toxic
  • severe_toxic
  • obscene
  • threat
  • insult
  • identity_hate

Link - https://www.kaggle.com/competitions/jigsaw-toxic-comment-classification-challenge

Setup

Model Used - BERT UNCASED

Download and save the folder in backend/models/

Model link - https://drive.google.com/drive/folders/1--mapYkARlwpwYeu6oTxP7Ly2csH_AW5?usp=sharing

Installation

pip install -r requirement.txt 

Twint Installation

pip3 install --user --upgrade git+https://github.com/twintproject/twint.git@origin/master#egg=twint

Backend - FLASK

cd backend
python main.py

  1. Addd Twitter Username in the input field

  2. Model will predict the tweets and display the result

twitter-account-analysis's People

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