Skip to main content

Analyzing Social Media Data in Python

In this course, you'll learn how to collect Twitter data and analyze Twitter text, networks, and geographical origin.

Start Course for Free
4 Hours14 Videos51 Exercises18,832 Learners4000 XPMarketing Analytics with Python Track

Create Your Free Account

GoogleLinkedInFacebook

or

By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.

Loved by learners at thousands of companies

Course Description

Twitter produces hundreds of million messages per day, with people around the world discussing sports, politics, business, and entertainment. You can access thousands of messages flowing in this stream in a matter of minutes. In this course, you will learn how to collect Twitter data and analyze tweet text, Twitter networks, and the geographical origin of the tweet. We'll be doing this with datasets on tech companies, data science hashtags, and the 2018 State of the Union address. Using these methods, you will be able to inform business and political decision-making by discovering the prevalence of important topics, the diversity of discussion networks, and a topic's geographical reach.
  1. 1

    Basics of Analyzing Twitter Data

    Free

    Why analyze Twitter, how to access Twitter APIs, and understanding Twitter JSON.

    Play Chapter Now
    Analyzing Twitter data
    50 xp
    Why Analyze Twitter Data?
    50 xp
    Uses of Twitter analysis
    50 xp
    Collecting data through the Twitter API
    50 xp
    Twitter APIs
    50 xp
    Setting up tweepy authentication
    100 xp
    Collecting data on keywords
    100 xp
    Understanding Twitter JSON
    50 xp
    Loading and accessing tweets
    100 xp
    Accessing user data
    100 xp
    Accessing retweet data
    100 xp
  2. 2

    Processing Twitter text

    How to process Twitter text.

    Play Chapter Now
    Processing Twitter text
    50 xp
    Tweet Items and Tweet Flattening
    100 xp
    A tweet flattening function
    100 xp
    Loading tweets into a DataFrame
    100 xp
    Counting words
    50 xp
    Finding keywords
    100 xp
    Looking for text in all the wrong places
    100 xp
    Comparing #python to #rstats
    100 xp
    Time series
    50 xp
    Creating time series data frame
    100 xp
    Generating mean frequency
    100 xp
    Plotting mean frequency
    100 xp
    Sentiment analysis
    50 xp
    Loading VADER
    100 xp
    Calculating sentiment scores
    100 xp
    Plotting sentiment scores
    100 xp
  3. 3

    Twitter Networks

    Network analysis with Twitter data.

    Play Chapter Now
    Twitter networks
    50 xp
    Types of Twitter networks
    50 xp
    Which direction is the arrow?
    50 xp
    Importing and visualizing Twitter networks
    50 xp
    Creating retweet network
    100 xp
    Creating reply network
    100 xp
    Visualizing retweet network
    100 xp
    Individual-level network metrics
    50 xp
    In-degree centrality
    100 xp
    Betweenness centrality
    100 xp
    Ratios
    100 xp
  4. 4

    Putting Twitter data on the map

    How to map Twitter data.

    Play Chapter Now
    Maps and Twitter data
    50 xp
    Motivations
    50 xp
    Comparisons
    50 xp
    Geographical data in Twitter JSON
    50 xp
    Coordinates and bounding boxes
    50 xp
    Accessing user-defined location
    100 xp
    Accessing bounding box
    100 xp
    Calculating the centroid
    100 xp
    Creating Twitter maps
    50 xp
    Creating Basemap map
    100 xp
    Plotting centroid coordinates
    100 xp
    Coloring by sentiment
    100 xp
    Congratulations!
    50 xp

In the following tracks

Marketing Analytics with Python

Datasets

Data Science Hashtag datasetState of the Union Reply Network datasetState of the Union Retweet Networking dataset

Collaborators

Greg Wilson
Kara Woo
David Campos
Shon Inouye
Eunkyung Park

Prerequisites

Data Manipulation with pandas
Alex Hanna Headshot

Alex Hanna

Computational Social Scientist

Alex Hanna is a computational social scientist working in the areas of politics, natural language processing, and fairness in machine learning and artificial intelligence.
See More

What do other learners have to say?

    Join over 11 million learners and start Analyzing Social Media Data in Python today!

    Create Your Free Account

    GoogleLinkedInFacebook

    or

    By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.