Analyzing Social Media Data in Python

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.

Collaborator(s)

Greg Wilson
Kara Woo
David Campos
Shon Inouye
Eunkyung Park

Prerequisites

pandas Foundations

Datasets

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.

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

Course Outline

1
Basics of Analyzing Twitter Data
Free

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

How to process Twitter text.
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Twitter Networks

Network analysis with Twitter data.
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Putting Twitter data on the map

How to map Twitter data.
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Course Instructor

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.

Collaborator(s)

Greg Wilson
Kara Woo
David Campos
Shon Inouye
Eunkyung Park

Courses

Tracks

Instructors

Analyzing Social Media Data in Python

Create Your Free Account

Alex Hanna

Collaborator(s)

Prerequisites

Datasets

Course Description

Course Outline

Basics of Analyzing Twitter Data

Analyzing Twitter data

Why Analyze Twitter Data?

Uses of Twitter analysis

Collecting data through the Twitter API

Twitter APIs

Setting up tweepy authentication

Collecting data on keywords

Understanding Twitter JSON

Loading and accessing tweets

Accessing user data

Accessing retweet data

Processing Twitter text

Processing Twitter Text

Tweet Items and Tweet Flattening

A tweet flattening function

Loading tweets into a DataFrame

Counting words

Finding keywords

Looking for text in all the wrong places

Comparing #python to #rstats

Time Series

Creating time series data frame

Generating mean frequency

Plotting mean frequency

Sentiment Analysis

Loading VADER

Calculating sentiment scores

Plotting sentiment scores

Twitter Networks

Twitter Networks

Types of Twitter networks

Which direction is the arrow?

Importing and visualizing Twitter networks

Creating retweet network

Creating reply network

Visualizing retweet network

Individual-level network metrics

In-degree centrality

Betweenness Centrality

Ratios

Putting Twitter data on the map

Maps and Twitter Data

Motivations

Comparisons

Geographical Data in Twitter JSON

Coordinates and bounding boxes

Accessing user-defined location

Accessing bounding box

Calculating the centroid

Creating Twitter maps

Creating Basemap map

Plotting centroid coordinates

Coloring by sentiment

Analyzing Social Media Data in Python

Course Instructor

Alex Hanna

Collaborator(s)