Sociometry: Social Network Analysis

If we carefully observe the drawing next to this text, it may seem to us like a human eye in formation: the colored part could be a pupil, while the many dots surrounding it make up the contour of the organ we use to detect light. If we were to be more specific, we would be able to distinguish certain wandering dots, moving away from the periphery that would eventually become other parts of the eye, not yet integrated into the cornea.

If we were to zoom in on the pupil, we may be able to notice that it is made up of many small dots joined together by edges; some dots have many lines connecting them to others, while others have few.

The sea of medusas, octopuses, and hybrids that each of these connections become slowly forms a web. Better yet, a network: a system sensitive to the changes in lighting, able to transform light into electric impulses that create a representation of reality. In this case, they give us a way of seeing virtual reality.

Sociograma #YoSoy132

Moving away from medusa metaphors, what we find in this image is not a visual representation of our optical organ, but a sociometric study of the virtual community formed around the social movement called #YoSoy132. Each dot represents a Twitter profile, while their interactions are drawn in the form of edges. The size of the dots is proportional to the amount of links (ins and outs) of each profile: the bigger ones mean a higher degree of connection, while the smaller ones represent a lower degree. Each color represents a different tribe. By tribe, we mean a group of people linked by conversation subjects that were discussed within the digital community and visually represented in the edges.

Last but not least, the contour of the cornea (the wandering dots we described earlier) symbolize the “nomads”: those members of the community that do not link to anyone else, but were also speaking of the same subject that moved the rest of the network.

After this explanation one may ask oneself, what’s the use of a sociometric study? And here lies the answer.

In general terms, sociometries allow us to take an X-ray of any cybernetic get-together. They use a statistical method coined by Harre and Lamb in 1990 called Analysis of the Main Components, in which the correlation between a number of variables within a dataset is reduced and visually represented. This means that we can obtain an image or graph from the information we feed the program, and thus identify patterns, links and correlations: basically, the image helps us identify the position that each individual actor holds within an online community, as well as the network’s overall structure (Sánchez, 1992).

In more poetic terms, the eye we discussed earlier gives us the opportunity to visualize digital tribes, Tribe Leaders (the dots with the greatest amount of links and influence), and the interactions of each of the individuals that makes up a digital community.

However, for this technique to be of any use, we must go beyond the structure and the position of each individual actor. The real task is to understand the sociometric map using social sciences. Psychology, sociology, and anthropology become tools that help the analyst understand the conversations and meanings exchanged by the members of each network. Just like Avatar’s Jake Sully, he or she must interact with the community to try to identify the social dynamics behind each interaction, be it online or face to face (through interviews, content analysis, etc.). Pandora’s clan life and meaning only became clear to Sully when he agreed to live as they lived.

Networks have become the reigning paradigm under which we see the world; the art of trying to understand them has become a discipline, much like cartography was centuries ago (Pisani & Piotet, 2009). However, we must never forget that the value of a network does not depend solely on its size, but on its members and the multiple ways in which they share meaning (Odlyzko & Tilly, 2005). In the end, the key is to use the graph as a map, and hermeneutics as a lens.