BigSee
Simplexity vs Multiplexity
larifari.org/notes/social-ties.html
Standard social network visualizations do not typically focus on the nature of relations or ties between individuals; thus, a single directional edge is often used to connect two person nodes. This edge does not represent the strength of the relation, or its nature. Are these two people co-workers, activity buddies, lovers? Is the relation recriprocal or one sided? To be fair to those researchers who devised these visualizations, the data given to them is probably representative of one only relation. Even if the data allowed for multiple relations to be known, it would probably be confusing to encode and display multiple relations, particularly in a large network; whereas a keep-it-simple approach could eschew the uninterpretability of the visualization. However, if we were to visualize the multiplexity of social ties, important patterns might emerge. In "Studying Online Social Networks," Garton et al. positions the deconstruction of social ties into bundles of disparate, directional relations as being key to understanding how individuals cluster in social networks, how these clusters overlap, and how clusters endure or fall apart. A key concept is the simplexity versus multiplexity of social ties. If a social tie features many different types of relations (e.g. co-workers, one tutors the other, watch baseball together), and if many of these relations are mutual, then the tie is known as a multiplex tie, and can be seen as durable. The durability of a single tie can impact the larger social network; for example, if a particular person is at a cut-point point and a tie is broken, a large subset of the network may drop out. It is also understood that individuals who are capable of relations not possessed by other members of his/her group or organization may serve the all important social role of gatekeeper. The aforementioned reasons make a compelling case for the inclusion of the simplexity/multiplexity of ties in social network visualizations. In the following sketch, we propose a way of including information about multiplexity into social networks, being sensitive not to overload the network visually
Simplexity vs Multiplexity
larifari.org/notes/social-ties.html
Standard social network visualizations do not typically focus on the nature of relations or ties between individuals; thus, a single directional edge is often used to connect two person nodes. This edge does not represent the strength of the relation, or its nature. Are these two people co-workers, activity buddies, lovers? Is the relation recriprocal or one sided? To be fair to those researchers who devised these visualizations, the data given to them is probably representative of one only relation. Even if the data allowed for multiple relations to be known, it would probably be confusing to encode and display multiple relations, particularly in a large network; whereas a keep-it-simple approach could eschew the uninterpretability of the visualization. However, if we were to visualize the multiplexity of social ties, important patterns might emerge. In "Studying Online Social Networks," Garton et al. positions the deconstruction of social ties into bundles of disparate, directional relations as being key to understanding how individuals cluster in social networks, how these clusters overlap, and how clusters endure or fall apart. A key concept is the simplexity versus multiplexity of social ties. If a social tie features many different types of relations (e.g. co-workers, one tutors the other, watch baseball together), and if many of these relations are mutual, then the tie is known as a multiplex tie, and can be seen as durable. The durability of a single tie can impact the larger social network; for example, if a particular person is at a cut-point point and a tie is broken, a large subset of the network may drop out. It is also understood that individuals who are capable of relations not possessed by other members of his/her group or organization may serve the all important social role of gatekeeper. The aforementioned reasons make a compelling case for the inclusion of the simplexity/multiplexity of ties in social network visualizations. In the following sketch, we propose a way of including information about multiplexity into social networks, being sensitive not to overload the network visually