GroupScope has developed proprietary algorithms, statistics, and metrics that can be applied to any relational dataset to give an insight into the structure of that data and the relative importance of the data points within it. Our formulas are based on research over the last 6+ years that started at Cornell University. In that time we have found innovative, lightweight processes to calculate interesting and important measures, and we are continually finding new and improved methods every time we encounter a problem and solve it. Because we developed these algorithms we can go beyond simply applying them to your data, and we can adjust and personalize them to specifically address the questions you have.

After we learn about your data from you and identify what information and relationships are important, we can provide you with metrics that target your needs exactly.

Statistics vs. Visuals
Usage of statistics is not limited to descriptions of the network images - where you begin by searching for a network and then examine the correlating statistics to describe it. Any statistics developed can also be applied by running reports on your data. If you need to search for data points that match a particular criteria or are above or below a certain threshold (high or low influence, users that serve as hubs for transmission of information, or structural importance or irrelevance for example) you can run these reports and then use the visuals to examine the matching results. The visuals and statistics can be used in combination - making both more valuable.