One thing about the Bass Model is networks are not going to make on explicit appearance, we'll enrich the analysis by bringing interaction structure in explicitly, and try to understand how things diffuse over time.
A benchmark model with no explicit social structure
Two actions/states/behaviors 0 and 1
F(t) fraction of the population who have adopted action 1 at time t
p: rate of spontaneous innovation/adoption
q: rate of imitation of adoption
$dF(t)/dt = (p + q F(t))(1 - F(t))$
$F(t) = (1 - e^{-(p+q)t}) / (1 + pe^{-(p+q)t}/q)$
Gives S-shape (if q > p) and tends to "1" in the limit as t becomes large
Initially only "p" matters, then "q" takes over
Eventually change slows as F(t) approaches 1
$$dF(t)/dt = (p + q F(t))(1 - F(t))$$
when F(t) nears 1, $dF(t)/dt = 0$
when F(t) = 0, $dF(t)/dt = p$
when F(t) = $\epsilon$, $dF(t)/dt = (p + q\epsilon)(1 - \epsilon)$
to get initial convexity: need $(p + q\epsilon)(1 - \epsilon) > p$
$q(1 - \epsilon) > p $, so initially need $q > p$
Reach of diffusion is bounded by the component structure
Some players or nodes are immune
Some links fail to transmit...
Answers questions of when get diffusion, and its extent (neither answered by simple Bass)