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Python Social Media Analytics

You're reading from   Python Social Media Analytics Analyze and visualize data from Twitter, YouTube, GitHub, and more

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781787121485
Length 312 pages
Edition 1st Edition
Languages
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Authors (3):
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Baihaqi Siregar Baihaqi Siregar
Author Profile Icon Baihaqi Siregar
Baihaqi Siregar
Siddhartha Chatterjee Siddhartha Chatterjee
Author Profile Icon Siddhartha Chatterjee
Siddhartha Chatterjee
Michal Krystyanczuk Michal Krystyanczuk
Author Profile Icon Michal Krystyanczuk
Michal Krystyanczuk
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Toc

Table of Contents (10) Chapters Close

Preface 1. Introduction to the Latest Social Media Landscape and Importance 2. Harnessing Social Data - Connecting, Capturing, and Cleaning FREE CHAPTER 3. Uncovering Brand Activity, Popularity, and Emotions on Facebook 4. Analyzing Twitter Using Sentiment Analysis and Entity Recognition 5. Campaigns and Consumer Reaction Analytics on YouTube – Structured and Unstructured 6. The Next Great Technology – Trends Mining on GitHub 7. Scraping and Extracting Conversational Topics on Internet Forums 8. Demystifying Pinterest through Network Analysis of Users Interests 9. Social Data Analytics at Scale – Spark and Amazon Web Services

Getting started with the toolset

Once you set up the whole environment, you can create your first project. If you use Linux or macOS machine, you can open a terminal and go to your working directory. Then, use the following command to create your project directory:

mkdir myproject 

On Windows machines, you can create the directory in the usual way without terminal.

At the same time, we initialize an empty repository in Git (in terminal on Linux or macOS, or in Git bash on Windows):

cd myproject 
git init

Then, you can open your directory in Sublime Text 2 using its GUI (Graphical User Interface) and create your first Python file. Now it's time to start working on a real project.

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