Let us now return to the Voter model. In the original model we had agents occupying two possible states. They chose their state simply by copying the choice made by their neighbors. Yet in most elections around the world more than two parties compete for the electoral vote. Furthermore it is hardly believable that any established supporter of any party would switch to following the opposing party over night. One way to account for these zealous supporters would be to introduce "agents with fixed state." Yet some strongly opinionated individuals do changes their beliefs, thus this would not be an ideal solution. Alternative approach was considered in [1]. In this paper a three state model is proposed, where the third state serves as intermediate stop for the agents switching between the two main states.

Previously discussed Granovetter threshold model is just one of the numerous simple collective action model. This time we continue the same topic by considering another, yet a bit more complex, riot model, which was proposed by Epstein in [1]. This model is rather interesting in a sense that it is not static as original Granovetter model is. It has interesting temporal dynamics builtin. In a recent paper by British mathematicians [2] this model was applied to explain the patterns observed in 2013 London riots.

Here on Physics of Risk we once again present you a model of collective action. Last time we have considered Standing Ovation Model by Miller and Page, in earlier years we have written a lot about Kirman and Bass models, as well as correspondence between them. There is another classic model, which will be covered in this post, which models human intention to join the collective political action with inherent risk. In this text we will consider a threshold model proposed by Mark Granovetter.

It has been a long time since last interactive model on Physics of Risk. This time we return to a problem we have already previously considered, but which we did not model.

From time to time almost everyone of us has an opportunity to go see a play. Afterwards everyone has to make a choice - to applaud or not to. It appears to be free choice, but actually it isn't as there are various social feedback loops in play. This problem was considered as a simple agent-based model in a paper by Miller and Page [1]. In this text we will briefly introduce you to it.

In this TED talk J.-B. Michel shares his experience in applying mathematical methods to history. According to him, mathematics combined with digitized historical data helps to reveal some interesting patterns. See for yourself!