Sentimental Analysis on COVID-19 Tweets using python

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在此指导项目中,您将:

Learn how to Preprocess text data for Sentimental Analysis

Learn how to Label text data with positive, negative and neutral sentiments

Learn to visualize the result of sentiment Analysis

Clock1 hour
Intermediate中级
Cloud无需下载
Video分屏视频
Comment Dots英语(English)
Laptop仅限桌面

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.

您要培养的技能

  • lambda
  • Python Programming
  • Plotly
  • Seaborn
  • Sentimental Analysis

分步进行学习

在与您的工作区一起在分屏中播放的视频中,您的授课教师将指导您完成每个步骤:

  1. importing our dataset

  2. preprocess and prepare our text data for Sentimental Analysis

  3. visualizing most common words using a bar chart.

  4. using NLTK module to produce Polarity scores for each tweet

  5. visualizing the result of our analysis using line chart

指导项目工作原理

您的工作空间就是浏览器中的云桌面,无需下载

在分屏视频中,您的授课教师会为您提供分步指导

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