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Sentimental Analysis on COVID-19 Tweets using python に戻る

Coursera Project Network による Sentimental Analysis on COVID-19 Tweets using python の受講者のレビューおよびフィードバック

4.6
35件の評価
8件のレビュー

コースについて

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....

人気のレビュー

YH
2020年11月12日

It was a good focused exercise on solving the problem statement

SR
2020年12月2日

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

フィルター:

Sentimental Analysis on COVID-19 Tweets using python: 1 - 8 / 8 レビュー

by Yamini H

2020年11月13日

It was a good focused exercise on solving the problem statement

by Sara R R

2020年12月3日

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

by Serhii D

2021年1月10日

Good starting project for data visualizing field.

by Meer M A

2021年2月5日

Great and helpful.

by Aniruddh M

2021年1月19日

Good one!

by Robert B

2021年2月25日

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.

by Şifa T

2021年6月22日

It was good and efficient to work on it. thanks

by Chung M

2021年3月7日

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!