Map Your Tweets, Posts or Links with Free NodeXL from Social Media Research Foundation - Book about Social Network Visualization

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A new book "Analyzing social media networks with NodeXL: Insights from a connected world" has just been published that guides readers through a step-by-step hands-on instructions to create social network maps and visualizations of collections of connections created through email, Twitter, flickr, Facebook, YouTube, the WWW and Wikis. The Social Media Research Foundation has released a free and open social network toolkit called "NodeXL" that allows anyone to make a social media network chart as easily as making a pie chart.

Analyzing social media networks with NodeXL

Making a social network chart is now as easy as making a pie chart with NodeXL.

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The Social Media Research Foundation (http://www.smrfoundation.org) announces the publication of "Analyzing social media networks with NodeXL: Insights from a connected world" on Morgan-Kaufmann (http://www.amazon.com/gp/product/0123822297?ie=utf8&tag=conneactio-20&linkcode=as2&camp=1789&creative=390957&creativeasin=0123822297).

The book is a step-by-step guide to understanding, mapping, and visualizing collections of connections created through social media. Readers will learn how to create a map of their own email connections, followers in Twitter, friends in Facebook, tags in flickr, and edits in Wikipedia using the free and open NodeXL add-in for Excel 2007/2010.

NodeXL (http://nodexl.codeplex.com) is the network overview, discovery and exploration add-in for Excel. It allows users to easily create social network diagrams with no programming required.

We live in a new sea of tweets, posts, blogs, and updates coming from a significant fraction of the people in the connected world. Our personal and professional relationships are now made up as much of texts, emails, phone calls, photos, videos, documents, slides, and game play as face-to-face interactions. Social media can be a bewildering stream of comments, a daunting fire hose of content. With better tools and a few key concepts from the social sciences, the social media swarm of favorites, comments, tags, likes, ratings, and links can be brought into clear focus to reveal key people and topics and sub-communities. As more social interactions move through machine-readable data sets new insights and illustrations of human relationships and organizations become possible. But new forms of data require new tools to collect, analyze, and communicate insights.

A new organization, the Social Media Research Foundation (http://www.smrfoundation.org), has been formed to develop open tools, open data sets, and foster open scholarship related to social media. The Foundation's current focus is on tools that enable social media network analysis and visualization from widely used services like email, Twitter, Facebook, flickr, YouTube and the http://www. The Foundation has released the free and open NodeXL project (http://www.codeplex.com/nodexl), a spreadsheet add-in that supports "network overview discovery and exploration". The tool fits inside your existing copy of Excel in Office 2007 or 2010 and makes creating a social network map similar to the process for making a pie chart.

Using NodeXL you can easily make a map of the public social media conversations around topics that matter to you. Maps of the connections among the people who recently said the name of a product, brand or event can reveal key positions and clusters in the crowd. Some people who talk about a topic are more in the "center" of the graph, they may be key influential members in the population. NodeXL makes it is a simple task to sort people in a population by their network location properties to find key people in core or bridge positions. NodeXL supports the exploration of social media with import features that pull data from personal email indexes on the desktop, twitter, flickr, youtube, facebook and WWW hyper-links. The tool allows non-programmers to quickly generate useful network statistics and metrics and create visualizations of network graphs.

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