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Mastering Social Media Mining with Python

You're reading from   Mastering Social Media Mining with Python Unearth deeper insight from your social media data with advanced Python techniques for acquisition and analysis

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Product type Paperback
Published in Jul 2016
Publisher Packt
ISBN-13 9781783552016
Length 338 pages
Edition 1st Edition
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Author (1):
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Marco Bonzanini Marco Bonzanini
Author Profile Icon Marco Bonzanini
Marco Bonzanini
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Table of Contents (10) Chapters Close

Preface 1. Social Media, Social Data, and Python FREE CHAPTER 2. #MiningTwitter – Hashtags, Topics, and Time Series 3. Users, Followers, and Communities on Twitter 4. Posts, Pages, and User Interactions on Facebook 5. Topic Analysis on Google+ 6. Questions and Answers on Stack Exchange 7. Blogs, RSS, Wikipedia, and Natural Language Processing 8. Mining All the Data! 9. Linked Data and the Semantic Web

Embedding the search results in a web GUI

In this section, we will expand on the first example in order to visualize the results of our search. As a means to show the items, we'll use a web page automatically generated on the fly so that we can display the profile image next to the display name for each person or page using a familiar interface. This visualization can help us disambiguate between different results that share the same display name.

In order to reach this goal, we will introduce Flask (http://flask.pocoo.org/), a micro framework for web development that allows us to rapidly produce a web interface.

Broadly speaking, Python and web development go hand in hand, and several web-related Python libraries have been around for many years, reaching an interesting level of maturity. Flask is relatively young compared to other frameworks, but it has also reached a level of maturity and has been adopted by a wide community. As web development is not a core concept of this book, we...

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