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Practical Data Analysis

You're reading from  Practical Data Analysis

Product type Book
Published in Oct 2013
Publisher Packt
ISBN-13 9781783280995
Pages 360 pages
Edition 1st Edition
Languages
Author (1):
Hector Cuesta Hector Cuesta
Profile icon Hector Cuesta
Toc

Table of Contents (24) Chapters close

Practical Data Analysis
Credits
Foreword
About the Author
Acknowledgments
About the Reviewers
www.PacktPub.com
Preface
1. Getting Started 2. Working with Data 3. Data Visualization 4. Text Classification 5. Similarity-based Image Retrieval 6. Simulation of Stock Prices 7. Predicting Gold Prices 8. Working with Support Vector Machines 9. Modeling Infectious Disease with Cellular Automata 10. Working with Social Graphs 11. Sentiment Analysis of Twitter Data 12. Data Processing and Aggregation with MongoDB 13. Working with MapReduce 14. Online Data Analysis with IPython and Wakari Setting Up the Infrastructure Index

Acquiring my Facebook graph


In Facebook the friends represent nodes and the relationship between two friends represents links but we can get a lot more information from it, such as gender, age, post list, likes, political affiliation, religion, and so on. And Facebook provides us with a complete Application Programming Interface (API) to work with its data. You may visit the following link for more information:

https://developers.facebook.com/

Another interesting option is the Stanford Large Network Dataset Collection, where we can find social networks' datasets well formatted and anonymized for educational proposes. Visit the following link for more information:

http://snap.stanford.edu/data/

Tip

Using the anonymized data, it is possible to determine whether two users have the same affiliations, but not what their individual affiliations represent.

Using Netvizz

In this chapter we don't get into the use of the Facebook API. The easiest method to get our Friends list is by using a third-party...

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