In this paper we study the modelling of consensus reach- ing in a `soft' environment, i.e. when the individual testi- monies are expressed as fuzzy preference relations. Here consensus is meant as the degree to which most of the experts agree on the preferences associated to the most relevant alternatives. First of all we derive a degree of dissensus based on linguistic quantifiers and then we in- troduce a form of network dynamics in which the quanti- fiers are represented by scaling functions. Next, assuming that the decision makers can express their preferences in a more flexible way, i.e. by means of triangular fuzzy num- bers, we describe the iterative process of opinion chang- ing towards consensus via the gradient dynamics of a cost function expressed as a linear combination of a dis- sensus cost function and an inertial cost function. Finally, some computer simulations are carried out together with a short description of a case study in progress. keywords group decision making; consensus; fuzzy pref- erence relations; linguistic quantifiers; fuzzy numbers; gradient dynamics.