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Based in Washington, D.C., the AIA (http://www.aia.org/) has been the leading professional membership association for licensed architects, emerging professionals, and allied partners since 1857. With nearly 300 state and local chapters, the AIA serves as the voice of the architecture profession and the resource for their members in service to society.

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• Organization: http://www.aia.org/
• Industry: Associations - Business/Professional
• Location: Washington DC, U.S.A.
• Date: March 2013
• Crawl Depth: Low
• Crawl time: 30 minutes
• Calibration algorithm: None
• Number of final participants: 84
• Number of final connections: 132
• Number of starting connections: 4,507
• Number of hotspots: 2
• Number of pivot points: 4
• Score value creation: 6.5% (VCCa = (Ndea x Ndia x Ncea x PRa x α)/(PRmax / PRa))
• Score http://marketinggrader.com: 68%
• Key recommendations: Implement continuous and expanding digital ecosystem monitoring. Implement coordinated social media marketing across region / globally. Integrate horizontal and vertical supply chain into digital ecosystem. Benchmark digital ecosystem against similar successful clusters and relevant comparative performance clusters. 

Crawl levels: 

Step 1: 1 Seed-URLs: http://www.aia.org/ (1000 link pairs maximum each / standard exclusion list)

Step 2: 3 Seed-URLs (ranked in order of frequency): http://www.aia.org, http://architectfinder.aia.org, http://careercenter.aia.org (1000 link pairs maximum each / standard exclusion list)

Step 3: 8 Seed-URLs (ranked in order of frequency): http://www.aia.org, http://careercenter.aia.org, http://architectfinder.aia.org, http://ams.aia.org, http://info.aia.org, http://foursquare.com, http://www.njht.org, http://howdesignworks.aia.org (1000 link pairs maximum each / standard exclusion list)

Cluster Analysis: 

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A cluster is a group of vertices that are densely connected to one another but sparsely connected to the rest of the graph. Network Predictor applies the Clauset-Newman-Moore cluster algorithm provided by NodeXL to identify clusters in the generated ecosystem. Each cluster not dominated by the presence of the seed URL is considered a pivot / tipping point since small changes in connectivity can result in large changes in the overall network structure. The connectivity changes should hereby focus on the key peripheral nodes of the clusters to achieve maximum leverage. The peripheral nodes easiest to influence are those of the second largest cluster. Social media nodes are neglected since these form dynamic communication channels that need to be addressed through digital marketing measures (see http://marketinggrader.com score / recommendations). The current value creation potential (VCCa = (Ndea x Ndia x Ncea x PRa x α)/(PRmax / PRa)) can most easily be improved by integrating clusters more tightly into the cluster of the seed URL.

• Total Number of Clusters: 5
• Pivot / Tipping Point Core URLs: http://www.flickr.com, http://www.njht.org, http://pinterest.com
• Pivot / Tipping Point Peripheral URLs of second largest cluster: http://convention.aia.org, http://howdesignworks.aia.org, http://www.foursquare.com, http://www.favorityarchitecture.com

Notes: 

• Vertex legend: Color based on Page-Rank (http://en.wikipedia.org/wiki/PageRank), size based on in-degree centrality (http://en.wikipedia.org/wiki/Centrality)
• Webcrawler Tool: Network Grader Webcrawler
• Visualization Tool: NodeXL http://nodexl.codeplex.com/
• Layout: Directed Fruchterman-Reingold http://wiki.gephi.org/index.php/Fruchterman-Reingold
• Visibility threshold: 2 incoming connections
• Duplicate connections removed: Yes
• Exclusion list applied: Yes

The immensity, complexity, and variety of our networks certainly provide interesting areas for creative thought and speculation. Can we learn anything about ourselves and the world in which we live by studying these networks? Today's network theorists argue that we can and they spend time studying these networks to try to understand the natural laws that govern their formation and structure. Malcolm Gladwell is one of these network theorists. More: http://www.stanford.edu/class/symbsys205/tipping_point.html