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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.

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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.
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In the following Tracks

Marketing Analytics in Python

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  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
For Business

Training 2 or more people?

Get your team access to the full DataCamp platform, including all the features.

In the following Tracks

Marketing Analytics in Python

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datasets

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

collaborators

Collaborator's avatar
Greg Wilson
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Kara Woo
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David Campos
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Shon Inouye
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Eunkyung Park
Alex Hanna HeadshotAlex 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.
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