Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Python Social Media Analytics

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

Arrow left icon
Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781787121485
Length 312 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Authors (3):
Arrow left icon
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
Arrow right icon
View More author details
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

Scope and process

The project and analysis in the chapter will cover the data gathered from the Twitter feeds through the Twitter API. Working with the API, the user has a selection of different endpoints (functionalities). We will focus on two of the most popular: the streaming and the search endpoints (REST API). The first one gives access to real-time data, showing tweets as they are published (in fact the access is to the sample, not all tweets). The latter allows to query historical tweets (up to about a week), based on several criteria, which is more suitable for a static analysis. The following are the steps to gather the data from the Twitter feeds:

  • Getting the data
  • Data pull
  • Data cleaning

Let us take a look at each one in detail.

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime