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学生对 Coursera Project Network 提供的 Sentimental Analysis on COVID-19 Tweets using python 的评价和反馈

4.6
35 个评分
8 条评论

课程概述

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....

热门审阅

YH
Nov 12, 2020

It was a good focused exercise on solving the problem statement

SR
Dec 2, 2020

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

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1 - Sentimental Analysis on COVID-19 Tweets using python 的 8 个评论(共 8 个)

创建者 Yamini H

Nov 13, 2020

It was a good focused exercise on solving the problem statement

创建者 Sara R R

Dec 3, 2020

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

创建者 Serhii D

Jan 10, 2021

Good starting project for data visualizing field.

创建者 Meer M A

Feb 5, 2021

Great and helpful.

创建者 Aniruddh M

Jan 19, 2021

Good one!

创建者 Robert B

Feb 25, 2021

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.

创建者 Şifa T

Jun 22, 2021

It was good and efficient to work on it. thanks

创建者 Chung M

Mar 7, 2021

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!