Found 51 repositories(showing 30)
tavishsrivastava
Predicting the winner of FIFA 2014
Mr-Chang95
The objective of this data science project is to conduct sentiment analysis on tweets related to the FIFA World Cup 2022. By analyzing the sentiment of tweets, the project aims to gain insights into the public's perception, emotions, and opinions surrounding the event.
parthnagarkar875
A random collection of 5.3 lac tweets on the FIFA world cup 2018 starting from the Round of 16 till the World Cup Final were analyzed using the TextBlob library which has a pre-trained built in lexicon to classify them as either positive, negative or neutral. A pie chart was used to show the percentage of positive, negative or neutral tweets related to the world cup.
No description available
chauhayu2511
Sentiment analysis on FIFA Worldcup 2022
Twitter Sentiment analysis on FIFA World Cup using Hadoop frameworks | Internship at Birlasoft Pvt Ltd, 2018
obie-china
No description available
No description available
The purpose of this project is to conduct a sentiment analysis on tweets related to the 2022 World Cup using two different approaches: the Vader sentiment analysis tool and a pre-trained Roberta model from Hugging Face.
Ananth09
A Sentiment analysis and prediction of possible direction of thought of tweets during FIFA World Cup 2022
RavikumarVadai
Sentiment analysis on VAR (video assistant referee) sytem in football games during the 2018 FIFA World Cup Russia
blazQ
⚽ World Cup Sentiment Analysis and Performance Prediction. Simple SA&ML project to try and predict the winner of the 2022 FIFA World Cup, written in Python using Scikit-learn.
zaheer6034
No description available
Qaiserfarooq285
No description available
EmreDinc10
Twitter Sentiment Analysis using Textblob on the dataset of tweets from FIFA 2022 World Cup
junedsaleh
Twitter Sentiment Analysis on FIFA-2022
agung-madani
No description available
No description available
sunilks12
No description available
ShafakatArnob
FIFA World Cup 2022 Sentiment Analysis with Deep Learning and LIME.
No description available
Sentiment analysis of FIFA World Cup 2022 tweets
No description available
enriquegomeztagle
No description available
An analysis of over 7000 Tweets about the 2022 World Cup teams
No description available
No description available
ishwari198
NLP | Sentiment analysis | Word Cloud | Data Cleaning
No description available
SuloveBhattarai
No description available