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Mining Social Media: Finding Stories in Internet Data

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BuzzFeed News Senior Reporter Lam Thuy Vo explains how to mine, process, and analyze data from the social web in meaningful ways with the Python programming language.

Did fake Twitter accounts help sway a presidential election? What can Facebook and Reddit archives tell us about human behavior? In Mining Social Media, senior BuzzFeed reporter Lam Thuy Vo shows you how to use Python and key data analysis tools to find the stories buried in social media.

Whether you're a professional journalist, an academic researcher, or a citizen investigator, you'll learn how to use technical tools to collect and analyze data from social media sources to build compelling, data-driven stories.

Learn how to:
  • Write Python scripts and use APIs to gather data from the social web
  • Download data archives and dig through them for insights
  • Inspect HTML downloaded from websites for useful content
  • Format, aggregate, sort, and filter your collected data using Google Sheets
  • Create data visualizations to illustrate your discoveries
  • Perform advanced data analysis using Python, Jupyter Notebooks, and the pandas library
  • Apply what you've learned to research topics on your own

  • Social media is filled with thousands of hidden stories just waiting to be told. Learn to use the data-sleuthing tools that professionals use to write your own data-driven stories.

    ISBN-13: 9781593279165

    Media Type: Paperback

    Publisher: No Starch Press

    Publication Date: 11-25-2019

    Pages: 208

    Product Dimensions: 6.90(w) x 9.10(h) x 0.60(d)

    Lam Thuy Vo is a senior reporter at BuzzFeed News where she focuses on the intersection of technology, society, and social media data. She has reported for The Wall Street Journal, Al Jazeera America, and NPR's Planet Money, telling economic stories across the US and throughout Asia. Vo has also spent over a decade as an educator, training newsrooms and developing courses for the Craig Newmark Graduate School of Journalism at CUNY.

    Table of Contents

    Introduction

    Part I: Data Mining
    Chapter 1: The Programming Languages You’ll Need to Know
    Chapter 2: Where to Get Your Data
    Chapter 3: Getting Data with Code
    Chapter 4: Scraping Your Own Facebook Data
    Chapter 5: Scraping a Live Site

    Part II: Data Analysis
    Chapter 6: Introduction to Data Analysis
    Chapter 7: Visualizing Your Data
    Chapter 8: Advanced Tools for Data Analysis
    Chapter 9: Finding Trends in Reddit Data
    Chapter 10: Measuring the Twitter Activity of Political Actors
    Chapter 11: Where to Go from Here