Mining Social Media-Finding Stories in Internet Data

Title Page
Copyright Page
Dedication
About the Author
BRIEF CONTENTS
CONTENTS IN DETAIL
ACKNOWLEDGMENTS
INTRODUCTION
What Is Data Analysis?
Who Is This Book For?
Conventions Used in This Book
What This Book Covers
Downloading and Installing Python
Getting Help When You’re Stuck
Summary
PART I: DATA MINING
1 THE PROGRAMMING LANGUAGES YOU’LL NEED TO KNOW
Frontend Languages
Backend Languages
Summary
2 WHERE TO GET YOUR DATA
What Is an API?
Using an API to Get Data
Answering a Research Question Using Data
Summary
3 GETTING DATA WITH CODE
Writing Your First Script
Running a Script
Planning Out a Script
Libraries and pip
Creating a URL-based API Call
Storing Data in a Spreadsheet
Running the Finished Script
Dealing with API Pagination
Templates: How to Make Your Code Reusable
Summary
4 SCRAPING YOUR OWN FACEBOOK DATA
Your Data Sources
Downloading Your Facebook Data
Reviewing the Data and Inspecting the Code
Analyzing HTML Code to Recognize Patterns
Writing Data into a Spreadsheet
Running the Script
Summary
5 SCRAPING A LIVE SITE
Messy Data
Scraping from a Live Website
Summary
PART II: DATA ANALYSIS
6 INTRODUCTION TO DATA ANALYSIS
The Process of Data Analysis
Bot Spotting
Getting Started with Google Sheets
Modifying and Formatting the Data
Aggregating the Data
Sorting and Filtering the Data
Merging Data Sets
Other Ways to Use Google Sheets
Summary
7 VISUALIZING YOUR DATA
Understanding Our Bot Through Charts
Conditional Formatting
Summary
8 ADVANCED TOOLS FOR DATA ANALYSIS
Using Jupyter Notebook
What Is pandas?
Summary
9 FINDING TRENDS IN REDDIT DATA
Clarifying Our Research Objective
Outlining a Method
Narrowing the Data’s Scope
Summarizing the Data
Summary
10 MEASURING THE TWITTER ACTIVITY OF POLITICAL ACTORS
Getting Started
Lambdas
Filtering the Data Set
Formatting the Data as datetimes
Resampling the Data
Plotting the Data
Summary
11 WHERE TO GO FROM HERE
Coding Styles
Statistical Analysis
Other Kinds of Analyses
Conclusion
Index