Social Media Analytics During Crises

I had the great opportunity to run a tutorial on social media analytics during crises at the 2016 HCIL Symposium at UMD this year.
As with my previous talk at MITH on Twitter + Ferguson, I wanted to give a talk that was informative about tools but also be hands-on enough, so attendees could see some easy analytics they could modify to answer their own questions.

The notebooks are available on Github, include data acquisition from Reddit, Facebook, and Twitter, and you can view them directly on github here: https://github.com/cbuntain/TutorialSocialMediaCrisis

This material includes:

Material Overview

Tutorial Introduction

  • Terror Data sets
    • Boston Marathon
      • 15 April 2013, 14:49 EDT -> 18:49 UTC
    • Charlie Hebdo
      • 7 January 2015, 11:30 CET -> 10:30 UTC
    • Paris Nov. attacks
      • 13 November 2015, 21:20 CET -> 20:20 UTC (until 23:58 UTC)
    • Brussels
      • 22 March 2016, 7:58 CET -> 6:58 UTC (and 08:11 UTC)

Data Acquisition

  • Topic 1: Introducing the Jupyter Notebook
    • Jupyter notebook gallery
  • Topic 2: Data sources and collection
    • Notebook: T02 – DataSources.ipynb
    • Data sources:
      • Twitter
      • Reddit
      • Facebook
  • Topic 3: Parsing Twitter data
    • Notebook: T03 – Parsing Twitter Data.ipynb
    • JSON format
    • Python json.load

Data Analytics

  • Notebook: T04-08 – Twitter Analytics.ipynb
  • Topic 4: Simple frequency analysis
    • Top hash tags
    • Most common keywords
    • Top URLs
    • Top images
    • Top users
    • Top languages
    • Most retweeted tweet
  • Topic 5: Geographic information systems
    • General plotting
    • Country plotting
    • Images from target location
  • Topic 6: Sentiment analysis
    • Subjectivity/Objectivity w/ TextBlob
  • Topic 7: Other content analysis
    • Topics in relevant data
  • Topic 8: Network analysis
    • Building interaction networks
    • Central accounts
    • Visualization