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Analyzing social media networks with NodeXL : insights from a connected world
Hansen D., Shneiderman B., Smith M., Morgan Kaufmann Publishers Inc., San Francisco, CA, 2010. 304 pp. Type: Book (978-0-123822-29-1)
Date Reviewed: Mar 23 2012

Recent statistics mention that 1.2 billion users worldwide now log on to social networks [1]. With the rapid expansion of the use of social networking environments, researchers have been trying to analyze and interpret multiple dimensions of user interactions in these environments. There are several freeware, open-source, and commercial tools available to analyze users’ online behavior and interactions, as well as their relationships with their peers, which constitute a social network.

This thorough and practical guide, written by experts in information studies, computer science, sociology, human-computer interaction, and cultural studies, presents the NodeXL tool, a free and open add-in for Excel. Its 15 chapters are grouped into three main parts: an introduction about social media and social network analysis; a brief tutorial of the NodeXL tool; and a practical example of how to use the tool for analyzing different social media systems, such as email, YouTube, and wikis, using built-in layout algorithms.

This is the only book in the field that provides step-by-step practical instructions on how to make the most of the tool when trying to analyze live data from social networking environments such as Facebook and Twitter. It is a great book for novices in social networking analysis and researchers who want guidance on how to analyze data from a specific type of social medium.

The only shortcoming is that the authors don’t provide a thorough comparison of the various available social network analysis (SNA) tools. Thus, although NodeXL is a usable tool with many features, the reader cannot easily understand its pros and cons when compared with other tools.

It would have been interesting if the authors had included more domain-specific cases. For example, they could have included a case from online education. Educators in networked learning communities receive very little support from tools to evaluate the flow of students’ learning activities and examine learners’ online behavior. An example of how NodeXL could be used to help educators analyze and interpret multiple dimensions of interaction in networked learning communities could be very interesting. The domain of interaction analysis in online education (educational data mining or learning analytics) has attracted a lot of attention lately [2].

This book can be valuable to instructors who want to teach SNA using NodeXL. Each chapter has an outline, an introduction, a practitioner’s summary, and a researcher’s agenda, which is very useful in teaching. In summary, this is an excellent book for both SNA novices and SNA practitioners and researchers who need clear theoretical and practical ideas about the way to analyze and interpret data coming from social networking environments.

Reviewer:  Symeon Retalis Review #: CR140006 (1208-0796)
1) Social networking is the most popular online activity. The New Age, December 26, 2011. http://www.thenewage.co.za/38836-1021-53-Social_networking_is_the_most_popular_online_activity (accessed March 22, 2012).
2) Romero, C.; Ventura, S.; Pechenizkiy, M.; Baker, R. S. J. d. Handbook of educational data mining. Taylor & Francis Group, Boca Raton, FL, 2011.
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