Russell - Mining the social web [data mining Facebook, Twitter, Linkedin, Google+, Github, and more

Beijing Cambridge Farnham Kln Sebastopol Tokyo

Some of the most basic assumptions this book makes about you as a reader is that you want to learn how to mine data from popular social web properties, avoid technology hassles when running sample code, and have lots of fun along the way. Although you could read this book solely for the purpose of learning what is possible, you should know up front that it has been written in such a way that you really could follow along with the many exercises and become a data miner once youve completed the few simple steps to set up a development environment. If youve done some programming before, you should find that its relatively painless to get up and running with the code examples. Even if youve never programmed before but consider yourself the least bit tech-savvy, I daresay that you could use this book as a starting point to a remarkable journey that will stretch your mind in ways that you probably havent even imagined yet.

To fully enjoy this book and all that it has to offer, you need to be interested in the vast possibilities for mining the rich data tucked away in popular social websites such as Twitter, Facebook, LinkedIn, and Google+, and you need to be motivated enough to download a virtual machine and follow along with the books example code in IPython Notebook, a fantastic web-based tool that features all of the examples for every chapter. Executing the examples is usually as easy as pressing a few keys, since all of the code is presented to you in a friendly user interface. This book will teach you a few things that youll be thankful to learn and will add a few indispensable tools to your toolbox, but perhaps even more importantly, it will tell you a story and entertain you along the way. Its a story about data science involving social websites, the data thats tucked away inside of them, and some of the intriguing possibilities of what you (or anyone else) could do with this data.

If you were to read this book from cover to cover, youd notice that this story unfolds on a chapter-by-chapter basis. While each chapter roughly follows a predictable template that introduces a social website, teaches you how to use its API to fetch data, and introduces some techniques for data analysis, the broader story the book tells crescendos in complexity. Earlier chapters in the book take a little more time to introduce fundamental concepts, while later chapters systematically build upon the foundation from earlier chapters and gradually introduce a broad array of tools and techniques for mining the social web that you can take with you into other aspects of your life as a data scientist, analyst, visionary thinker, or curious reader.

Some of the most popular social websites have transitioned from fad to mainstream to household names over recent years, changing the way we live our lives on and off the Web and enabling technology to bring out the best (and sometimes the worst) in us. Generally speaking, each chapter of this book interlaces slivers of the social web along with data mining, analysis, and visualization techniques to explore data and answer the following representative questions:

The answers to these basic kinds of questions often yield valuable insight and present lucrative opportunities for entrepreneurs, social scientists, and other curious practitioners who are trying to understand a problem space and find solutions. Activities such as building a turnkey killer app from scratch to answer these questions, venturing far beyond the typical usage of visualization libraries, and constructing just about anything state-of-the-art are not within the scope of this book. Youll be really disappointed if you purchase this book because you want to do one of those things. However, this book does provide the fundamental building blocks to answer these questions and provide a springboard that might be exactly what you need to build that killer app or conduct that research study. Skim a few chapters and see for yourself. This book covers a lot of ground.

Python-Centric Technology

This book intentionally takes advantage of the Python programming language for all of its example code. Pythons intuitive syntax, amazing ecosystem of packages that trivialize API access and data manipulation, and core data structures that are practically shows a view of one notebook.

Figure 1. Overview of IPython Notebook; a dashboard of notebooks