Path and Component Metrics, new in NodeXL v.1.0.1.109

NodeXL has updated again (v.1.0.1.109) with new network metrics.  The application now calculates path length data for your network, reporting the Maximum Geodesic Distance and the Average Geodesic Distance.  The list of overall metrics NodeXL creates includes: Vertices (the number of nodes in the graph), Unique Edges, Edges With Duplicates, Total Edges, Self-Loops (Edges that point back at the node from which they originate), Connected Components (each set of connected nodes that are not connected to another set of nodes), Single-Vertex Connected Components (all the “singletons” of just one node in a component), Maximum Vertices in a Connected Component (the size of the “Giant” component), Maximum Edges in a Connected Component (the density of the “Giant” component), Maximum Geodesic Distance (Diameter) (the longest path that can be uniquely walked through the graph), Average Geodesic Distance (the average distance between two nodes in the graph (compare this to the “six degrees” standard), Graph Density (the density of the complete network).

More metrics and details on existing metrics are on the way!

What metrics do you need?

Conference: Web 2.0 in San Francisco – “Beyond Buzz: On Measuring a Conversation” with Kate Niederhoffer

2009 Web 2.0 San Francisco Logo

I will be speaking with Kate Niederhoffer from Dachis at Web 2.0 Expo Wednesday, April 1st at 10.50 in San Francisco.  We will be speaking about:

Beyond Buzz: On Measuring a Conversation
http://www.web2expo.com/webexsf2009/public/schedule/detail/6273

What is the most meaningful way to understand and measure a dialogue? As marketing transforms from a broadcast model to a conversational one, which constructs should be captured and how do you measure them? Is it necessary to make a distinction between the metrics used to tap into the value of a conversation per se and the ROI of a social media marketing campaign?

The proposed presentation offers new strategies to think about and tap into the depth of interactions and emotional connections people have online. Beyond buzz levels, sentiment, and other core metrics typically provided by brand monitoring solutions, the presentation will offer methods to understand a conversation: how emotional is it, how in synch are the constituents, how intimately do they relate to the brand or product? How much trust do the constituents reveal?

Marketing efforts that take advantage of technology to enable community and collaboration render traditional metrics limiting, at best. Traditional metrics have been optimized for more passive exposure to a specific message, frequency of exposure is considered a proxy for relevance; and, the premium is on reach over quality.

Primarily due to its more participative dynamic, a conversation engages constituents unlike static messaging. As many in the industry have noted, a natural development is to measure engagement. However, there is little consensus on what engagement means and how it can be measured. Often it is calculated by merely adding traditional metrics, assuming more is better.

The presentation will introduce new constructs and present case studies with empirical research demonstrating more valuable, still measurable constructs than the core metrics currently in use.