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Sentimental Analysis on COVID-19 Tweets using python(으)로 돌아가기

Coursera Project Network의 Sentimental Analysis on COVID-19 Tweets using python 학습자 리뷰 및 피드백

4.6
별점
35개의 평가
8개의 리뷰

강좌 소개

By the end of this project you will learn how to preprocess your text data for sentimental analysis. So in this project we are going to use a Dataset consisting of data related to the tweets from the 24th of July, 2020 to the 30th of August 2020 with COVID19 hashtags. We are going to use python to apply sentimental analysis on the tweets to see people's reactions to the pandemic during the mentioned period. We are going to label the tweets as Positive, Negative, and neutral. After that, we are going to visualize the result to see the people's reactions on Twitter. Note: This project works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

최상위 리뷰

YH
2020년 11월 12일

It was a good focused exercise on solving the problem statement

SR
2020년 12월 2일

Great idea! Loved to follow you along on this project!

필터링 기준:

Sentimental Analysis on COVID-19 Tweets using python의 8개 리뷰 중 1~8

교육 기관: Yamini H

2020년 11월 13일

It was a good focused exercise on solving the problem statement

교육 기관: Sara R R

2020년 12월 3일

Great idea! Loved to follow you along on this project!

교육 기관: Serhii D

2021년 1월 10일

Good starting project for data visualizing field.

교육 기관: Meer M A

2021년 2월 5일

Great and helpful.

교육 기관: Aniruddh M

2021년 1월 19일

Good one!

교육 기관: Robert B

2021년 2월 25일

Excellent overview of the topic of analyzing twitter data for creating a basic sentiment dataset and creation of related visualizations using Seaborn, and Plotly Express.

교육 기관: Şifa T

2021년 6월 22일

It was good and efficient to work on it. thanks

교육 기관: Chung M

2021년 3월 7일

I love the step-by-step approach to conduct sentiment analysis in this course. The instructor guided me through all the code and therefore let me experiment on my own. However, I would appreciate if he could give more explanation on the theory (polarity score) and code concept (''join). Apart from the sentiment result of 'positive', 'negative' and 'neutral', everything else is the same as the Twitter Sentiment Analysis beginner course. I hope it would offer at least the concept of polarity score. Thank you for offering the course anyway!