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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
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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 FREE CHAPTER 2. Harnessing Social Data - Connecting, Capturing, and Cleaning 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 the data


Forums do not provide programmatic interfaces (APIs) to capture data. However, you can connect to the website as a user to see all the conversations and collect data. The process of data extraction automatically from websites is called 'web scraping'.

Introduction to scraping

Since the beginning of the web, web scraping has been the main challenge for anyone who wanted to exploit the richness of information available on the Internet. In the very beginning, very few APIs were available and people used to copy the content of websites by just using copy-paste schema. Then, some programmatic tools were created to follow links (crawling) and extract the content from web pages (scraping). The information was structured by using text patterns (regex) or DOM (Document Object Model) parsing methods. More recently, the development of semantic analysis tools and artificial intelligence enabled alternative approaches, which are much more efficient and closer to human understanding and...

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