Conclusion

 

3-D Node-Links

 

"Building and Analyzing Node-Link Diagrams to Understand Social Networks" was created to offer a high-level view of what node-link diagrams representing social networks are...and some of their applications in the world. My aim was to both acquire a sense of node-link diagrams used in the context but also to provide F2F audience members and site visitors an "intuition" for such data visualizations.

This presentation relied extensively on existing information out in the "wild" of the Internet and World Wide Web (WWW). To actually begin doing work in this area suggests plenty of prior preparatory work and background knowledge and some hardiness in acquiring knowledge of how to use a new technology.

It is hoped in the next round, you will be able to see how a social network research software works.

The statistical tools for the analysis and visualization of social networks are evolving at this very moment. In a future presentation or publication, I hope to explore those in more detail, too.

Now, to make something of all this... :)

 

"Simple Network Analysis with UCINET" by Mo-Han Hsieh (MIT's OpenCourseware)

 

(Note: Per this presenter's initial experiences with UCINET, it makes more sense to start with an Excel table. Then, after the table is placed in UCINET and visualized, one can return to the table and make adjustments to the structure, labels, and informational cells describing the relationships. It helps to explore different visualizations of the data, such as turning a social network into a ring lattice or "circle." Assume correctly that there's a lot to learn and that as one learns, one may slowly bring in complexity. A social network visualization tells an angle of a story, but there's always more to a story than one aspect.)

 

 

Dr. Shalin Hai-Jew, Instructional Designer

iTAC

Kansas State University

shalin@k-state.edu

785-532-5262

 

 

 

Thanks to Jerome S. for his introduction of the UCINET software technology and his cool social network visualizations. Thanks also to Phyllis Epps and Dr. Rebecca Gould for encouraging my curiosity about this technology and allowing me some space to pursue this interest.

 

Please consider!  

 

Call for Chapter Proposals: Packaging Digital Information for Enhanced Learning and Analysis: Data Visualization, Spatialization, Predictiveness, and Multidimensionality

 

Call for Chapter Proposals: Remote Workforce Training: Effective Technologies and Strategies