Mining the Social Web: Data Mining Facebook,Twitter,LinkedIn,Instagram,GitHub,and More
Authors: Matthew A. Russell – Mikhail Klassen
ISBN-10: 1491985046
ISBN-13: 9781491985045
Edition 版次: 3
Publication Date 出版日期: 2019-01-17
Print Length 页数: 432 pages
Book Description
By finelybook
Mine the rich data tucked away in popular social websites such as Twitter,Facebook,LinkedIn,and Instagram. With the third edition of this popular guide,data scientists,analysts,and programmers will learn how to glean insights from social media—including who’s connecting with whom,what they’re talking about,and where they’re located—using Python code examples,Jupyter notebooks,or Docker containers.
In part one,each standalone chapter focuses on one aspect of the social landscape,including each of the major social sites,as well as web pages,blogs and feeds,mailboxes,GitHub,and a newly added chapter covering Instagram. Part two provides a cookbook with two dozen bite-size recipes for solving particular issues with Twitter.
Get a straightforward synopsis of the social web landscape
Use Docker to easily run each chapter’s example code,packaged as a Jupyter notebook
Adapt and contribute to the code’s open source GitHub repository
Learn how to employ best-in-class Python 3 tools to slice and dice the data you collect
Apply advanced mining techniques such as TFIDF,cosine similarity,collocation analysis,clique detection,and image recognition
Build beautiful data visualizations with Python and JavaScript toolkits
Preface
1.A Guided Tour of the Social Web
Prelude
1. Mining Twitter. Exploring Trending Topics,Discovering What People Are Talking About,and More
2. Mining Facebook: Analyzing Fan Pages,Examining Friendships,and More
3. Mining Instagram: Computer Vision,Neural Networks,Object Recognition,and Face Detection
4. Mining Linkedin: Faceting Job Titles,Clustering Colleagues,and More
5. Mining Text Files: Computing Document Similarity,Extracting Collocations,and More
6. Mining Web Print Length 页数: Using Natural Language Processing to Understand Human Language,Summarize Blog Posts,and More
7. Mining Mailboxes: Analyzing Who’s Talking to Whom About What,How Often,and More
8. Mining GitHub: Inspecting Software Collaboration Habits,Building Interest Graphs,and More
1. Twitter Cookbook
9. Twitter Cookbook
ll. Appendixes
A. Information About This Book’s Virtual Machine Experience
B. OAuth Primer
C. Python and Jupyter Notebook Tips and Tricks
Index
