Social Network Analysis 101
Social Network Analysis (SNA) is already common and accepted in other industries, such as Cell Phones, where companies know that as soon as one person makes a change, their friends follow. Lnx is a leader in adapting SNA to the intricacies and nuances of life science communities where the need is just as great but the complexities of the industry make the process more difficult.
Although “social networks” is now a common phrase, social network analysis is less well understood. SNA is an academic discipline that emerged in the 1930s to understand social systems. It only works when an entire community is modeled. If there are 50,000 people, you need to model all their connections. It’s a mathematical fact that you can’t estimate a community from surveys any more than you can estimate a snowflake from a raindrop. Only the advent of powerful computing technologies makes SNA commercially practical and Lnx is a pioneer in developing the toolset necessary to apply the methods to life science communities. Lnx works closely with academic centers around the world to develop new SNA tools and techniques and to ensure that we stay in front of emerging discoveries.
Most of the “network maps” seen today in life science circles are simply graphical depictions of survey results or other limited data sources. One common type of map is an “influence map” that is simply a depiction of survey results where respondents report influence. These simplistic types of maps are not products of SNA and do not “scale” to the entire community. This type of mapping has nothing to do with what Lnx does although some of the end products may be indistinguishable at a glance.
Social Network Analysis represents people as “nodes” and anything that draws them together (such as a publication or committee membership) as a “link” between them. In simple terms, the Lnx system counts everybody’s links to everybody else and then determines how far everybody is from everybody else. By applying various mathematical algorithms, Lnx calculates what are generally referred to as centrality measures. These measures reflect the relative importance of each person’s connections, their relative closeness to the center of the community, and how important they are to connecting different sub-groups (“betweeness”).
Lnx computers draw all these connections to reveal striking visual patterns that are not discoverable by looking at the mass of data. Groups of individuals (Workcircles™) become readily apparent as well as the structure of the community. Lnx also captures all the data associated with each individual. This may include organizational affiliations, place of work, physical location, publications, clinical trials, etc. In viewing Lnx maps, these attributes are also observable and analysts can easily determine which entities or activities are bringing people together.
Lnx has also developed and validated a proprietary method to identify an individual’s particular role in the community and, by extension, to identify target segments. Target segmentation translates SNA calculations into understandable and actionable information that allows clients to find the type of KOLs they need and, conversely, to understand the needs of the KOLs they work with so that they can build stronger relationships.
Once an entire community is mapped, it’s possible to examine any of its components in great detail or carve them out for closer inspection and analysis. For example, data can be sorted geographically to create a national or regional map. While the mapping process is an essential step in calculating measures, the results can be converted back into data that can be sorted, manipulated and even added to and remapped, as needed.