Research into diffusion processes permeates disciplines as diverse as computer science, anthropology, sociology, economics, epidemiology, chemistry, and physics. Much recent work, in the last fifty years or so, has been explicitly network oriented and has sought to better understand how network topology and transmission mechanisms determine properties such as the rate of diffusion and the various thresholds at which diffusion processes become self-sustaining.
Despite the many apparent similarities between different diffusion processes, it is important to be attentive to the particulars of each kind of diffusion process. Commercial products diffuse among consumers in ways different than do news articles or news topics in the blogosphere (see Dynamics of the News Cycle). Behaviors like smoking spread across networks of friends in both similar and contrasting ways as those of sexually transmitted diseases. And routing information in a sensor network propagates differently than routing information in a mobile phone network.
Diffusion of Semantic Content
The diffusion of information or more generally semantic content has been a cross-disciplinary concern, and has been treated in a variety of ways, depending on the domain of application. It is generally recognized that such content exhibits properties that distinguishes it from the diffusion of other phenomena. For example, it is recognized that the sharing of semantic content, unlike commodities, does not necessarily incur a consequent loss of that content for the sharer, and that information is often shared preferentially with those for whom it may be of interest or desired.
Nonetheless, in more general settings the implications of the properties of semantic content for its diffusion has to my knowledge not yet been formally investigated. Content is typically treated as a non-relational item whose diffusion-mechanism is essentially content-neutral, except perhaps in its differential transmissibility or mutability. Furthermore, it frequently restricts its models to the diffusion of isolated pieces of content in an otherwise content-less context. Consequently, it confounds the diffusion of content vehicles with the diffusion of the semantic content itself, treating content vehicles as having an intrinsic meaning or significance.
It is true that the transmission of content vehicles is easier to understand, and that this simple approach probably does a fair job of approximating the diffusion of semantic content at a unit of content or level of abstraction at which the applicability of a more rigorous approach may not be either readily apparent or especially necessary. Yet it has the unfortunate effect of potentially blinding us to the way in which the relation between contents and cognition (or computation) can generate a second, more leaky, means of content diffusion, or can inhibit or transform content. For example, it is entirely possible for multiple agents in a network to independently infer the same piece of information without that piece of information ever having been explicitly communicated to them. It is also, I might add, entirely possible for two agents to receive the same communications and infer entirely different things, or fail to interpret the message correctly, as anyone who has had to try to collaborate with others by email can readily attest.
 See my recent blog post Processes of Diffusion in Networks
 Unlike disease, which neither the giver or receiver desires!