Matthew A. Russell

Matthew Russell

Provides information on data analysis from a vareity of social networking sites, including Facebook, Twitter, and LinkedIn.

Analyzing Data from Facebook, Twitter, LinkedIn, and Other Social Media Sites

Mining the Social Web

Mining the Social Web: Data Mining Facebook, Twitter, Linkedin, Google+, Github, And More

Want to tap the tremendous amount of valuable social data in Facebook, Twitter, LinkedIn, and Google+? This refreshed edition helps you discover who’s making connections with social media, what they’re talking about, and where they’re located. You’ll learn how to combine social web data, analysis techniques, and visualization to find what you’ve been looking for in the social haystack—as well as useful information you didn’t know existed. Each standalone chapter introduces techniques for mining data in different areas of the social Web, including blogs and email. All you need to get started is a programming background and a willingness to learn basic Python tools. Get a straightforward synopsis of the social web landscape Use adaptable scripts on GitHub to harvest data from social network APIs such as Twitter, Facebook, LinkedIn, and Google+ Learn how to employ easy-to-use Python tools to slice and dice the data you collect Explore social connections in microformats with the XHTML Friends Network Apply advanced mining techniques such as TF-IDF, cosine similarity, collocation analysis, document summarization, and clique detection Build interactive visualizations with web technologies based upon HTML5 and JavaScript toolkits "A rich, compact, useful, practical introduction to a galaxy of tools, techniques, and theories for exploring structured and unstructured data." --Alex Martelli, Senior Staff Engineer, Google

How can you tap into the wealth of social web data to discover who’s making connections with whom, what they’re talking about, and where they’re located? With this expanded and thoroughly revised edition, you’ll learn how to acquire, analyze, and summarize data from all corners of the social web, including Facebook, Twitter, LinkedIn, Google+, GitHub, email, websites, and blogs. Employ the Natural Language Toolkit, NetworkX, and other scientific computing tools to mine popular social web sites Apply advanced text-mining techniques, such as clustering and TF-IDF, to extract meaning from human language data Bootstrap interest graphs from GitHub by discovering affinities among people, programming languages, and coding projects Build interactive visualizations with D3.js, an extraordinarily flexible HTML5 and JavaScript toolkit Take advantage of more than two-dozen Twitter recipes, presented in O’Reilly’s popular "problem/solution/discussion" cookbook format The example code for this unique data science book is maintained in a public GitHub repository. It’s designed to be easily accessible through a turnkey virtual machine that facilitates interactive learning with an easy-to-use collection of IPython Notebooks.

Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More

Millions of public Twitter streams harbor a wealth of data, and once you mine them, you can gain some valuable insights. This short and concise book offers a collection of recipes to help you extract nuggets of Twitter information using easy-to-learn Python tools. Each recipe offers a discussion of how and why the solution works, so you can quickly adapt it to fit your particular needs. The recipes include techniques to: Use OAuth to access Twitter data Create and analyze graphs of retweet relationships Use the streaming API to harvest tweets in realtime Harvest and analyze friends and followers Discover friendship cliques Summarize webpages from short URLs This book is a perfect companion to O’Reilly's Mining the Social Web.

Distilling Rich Information from Messy Data

21 Recipes for Mining Twitter

Of all the Ajax-specific frameworks that have popped up in recent years, one clearly stands out as the industrial strength solution. Dojo is not just another JavaScript toolkit—it's the JavaScript toolkit—and Dojo: The Definitive Guide demonstrates how to tame Dojo's extensive library of utilities so that you can build rich and responsive web applications like never before. Dojo founder Alex Russell gives a foreword that explains the "why" of Dojo and of this book. Dojo provides an end-to-end solution for development in the browser, including everything from the core JavaScript library and turnkey widgets to build tools and a testing framework. Its vibrant open source community keeps adding to Dojo's arsenal, and this book provides an ideal companion to Dojo's official documentation. Dojo: the Definitive Guide gives you the most thorough overview of this toolkit available, showing you everything from how to create complex layouts and form controls closely resembling those found in the most advanced desktop applications with stock widgets, to advanced JavaScript idioms to AJAX and advanced communication transports. With this definitive reference you get: Get a concise introduction to Dojo that's good for all 1.x versions Well-explained examples, with scores of tested code samples, that let you see Dojo in action A comprehensive reference to Dojo's standard JavaScript library (including fundamental utilities in Base, Dojo's tiny but powerful kernel) that you'll wonder how you ever lived without An extensive look at additional Core features, such as animations, drag-and-drop, back-button handling, animations like wipe and slide, and more Exhaustive coverage of out-of-the-box Dijits (Dojo widgets) as well as definitive coverage on how to create your own, either from scratch or building on existing ones An itemized inventory of DojoX subprojects, the build tools, and the DOH, Dojo's unit-testing framework that you can use with Dojo—or anywhere else If you're a DHTML-toting web developer, you need to read this book—whether you're a one-person operation or part of an organization employing scores of developers. Dojo packs the standard JavaScript library you've always wanted, and Dojo: The Definitive Guide helps you transform your ideas into working applications quickly by leveraging design concepts you already know.

The Definitive Guide

Dojo: The Definitive Guide

Mikhail Klassen

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

Matthew A. Russell

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