Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
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
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

Arrow left icon
Product type Paperback
Published in Jul 2016
Publisher Packt
ISBN-13 9781783552016
Length 338 pages
Edition 1st Edition
Languages
Concepts
Arrow right icon
Author (1):
Arrow left icon
Marco Bonzanini Marco Bonzanini
Author Profile Icon Marco Bonzanini
Marco Bonzanini
Arrow right icon
View More author details
Toc

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

NLP Basics


This section tries to scratch the surface of the complex field of NLP. The previous chapters have mentioned some of the basics that are necessary for dealing with textual data (for example, tokenization) without going too much into the details. Here, we'll try to go one step further into the basic understanding of this discipline. Due to its complexity and many aspects, we're taking a pragmatic approach and only scratching the surface of the theoretical foundations in favor of practical examples.

Text preprocessing

An essential part of any NLP system is the preprocessing pipeline. Before we can perform any interesting task on a piece of text, we must first convert it in a useful representation.

In the previous chapters, we already performed some analysis on the textual data without digging into the details of text preprocessing, but instead using the common tools with a pragmatic approach. In this section, we'll highlight some of the common preprocessing steps and discuss their role...

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
Banner background image