Celebrity Tweet Analysis and Visualization

Parse any celebrity's tweets from their Twitter Account with Tweepy, apply sentiment analysis, and visualize common patterns in their Tweets! We chose Donald Trump when we built the project, but due to his account suspension, change Trump to any celebrity!

TECHNOLOGIES

Data Visualization
Pandas
MatPlotLib
Data Analysis

WATCH TIME

35 minutes

LEVEL

All

Overview

This project is a beginner-friendly Python and Data Science application focused on using the Tweepy module to parse, analyze and visualize tweets. We’ll get a list of all of the latest tweets, create a data frame, and build visualizations on the number of likes, sentiment analysis of the tweets, and finally a word map on the common words used.

Project Tasks

Welcome to the project!

2 min

Setting up Twitter Authentication with Tweepy

We will be setting up Twitter authentication to get the information needed for the rest of the project.

8 min

Analyzing and Visualizing Tweet Sentiment

Applying sentiment analysis on daily tweets using the Vader sentiment intensity analyzer function.

9 min

Generating a Word Cloud of Common Words

Creating a Word Cloud to visualize the most common words in tweets.

6 min

Visualizing Number of Likes Per Tweet

Plotting a histogram of the number of likes across our celebrity's tweets.

5 min

Creating our Tweet DataFrame

Creating the DataFrame from Twitter data to be parsed later on in this project.

8 min

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