SDMA - Project : Comparaison of several movies in different type with same notes

Hello and welcome to the Git of SDMA-Project.

API for Tweeter

• Twint project: GitHub Page of Twint.
• Tuto for Twint Usage https://pielco11.ovh/posts/twint-osint/

Links for classifier and emotion :

• Sentiment-Analysis-of-Text-Data-Tweets : GitHub Page of Sentiment Analysus of Text Data Tweets
• imdb-sentiment-analysis : GitHub Page of imdb-sentiment-analysis

Subject

The goal of this project is to collect informations on Twitter about some films. Once collected we will analyse these informations and guess the emotion and reaction from Twitter users about each film. We will evaluate the score for each film with our machine learning and compare this score with the official IMDb score.

Plan

Thib: Je propose de prendre la tache 1 et 2, est ce que c'est ok pour vous ?

1. Collect tweet - scrolling / filter on #'film name' (Thibaud)
2. Preprocess on each tweet (Thibaud)
3. Train our classifier (must find data to train classifier with emotion) (Yurui)
4. Predict the emotion for each tweet (Yurui)
5. Predict a score with the emotion level (score /10) (Matthieu)
6. Compare this score with the official IMDb score (Matthieu)

API to get Official IMDb score

https://imdbpy.github.io/