Small Group Virtual Dynamics
Responsible: Andrea Guazzini, Alessandro Cini
Beyond their common use for interpersonal communication, chatlines (also chat-rooms) can be formalized as dynamic systems with heuristics. We have studied chatlines in the framework of social networks. The design and data analysis of chatlines opens a new interesting research direction in social network studies. It provides the opportunity of studying the dynamics of human social behaviour in experimental ’controlled’ (or nearly controlled) conditions. Our study aims to point out both the analogy with physical systems of interacting objects and the social network emerging properties linked to the existence of different communication patterns and usage of different heuristics in the participants. We describe guidelines for effective implementation of a chatline in controlled experimental conditions. We identified several parameters which represent meaningful statistical estimators of the activity of the network and we computed the correlation of these parameters and measures of network statistics.
Cognitive Approach to Community Detection
Responsible: Andrea Guazzini, Emanuele Massaro

Detecting communities is a task of great importance in many disciplines, namely sociology, biology and computer science, where systems are often represented as graphs. Community detection is linked to clustering of data: many clustering methods establish links among representa 
tive points that are nearer than a given threshold, and then proceed in identifying communities on the resulting graphs. Given a graph, a community is a group of vertices “more linked” than between the group and the rest of the graph. This is clearly a  lousy definition, and indeed, or a connected graph, there is not a clear distinction between a community and a rest of the graph. In general, there is a continuum of nested communities whose boundaries are somewhat arbitrary: the structure of communities can be seen as a hierarchical dendogram. A community-detection algorithm should therefore retu
rn different “views”, according to the value of some control parameter. Due to the arbitrariness of the definition, such “views” are relevant if they are not crucially dependent on the precise value of the parameters, i.e., if communities appears as “plateaus” when varying the control parameter.
We want to explore the behavior of exploratory methods inspired to human heuristics, in the hope of exploiting the “social knowledge” of human mind and also for developing more “natural” human-computer interfaces. Clearly, we do not pretend to simulate the real human behavior, but only to study the behavior of simplified models inspired to it. In particular, we deal with the task of identifying communities in an existing graphs, using a local algorithm and not relying on global quantities like betweenness, centrality, etc. An individual is simply modeled as a memory and a set of connections to other individuals. We explore two different approaches: in the first, information about neighboring nodes if propagated and elaborated locally, but the connections do not change. In the second approach, information is not elaborated while it is the wiring that is varied with the result of direct ly connecting to a “central node”. B
oth processes can be considered implementations of the availability heiristic, which is simply the assumption that the most vivid or easily recallable information give an accurate estimate of the frequency of the related event in the population.
In both approaches, the “learning” (nonlinear) phase is modeled after competition in chemical/ecological world. This can be considered an implementation of the anchoring heuristics, in which the judgment or the action is dominated by one or very few pieces of information, the most relevant ones.
Responsible: Andrea Guazzini, Franco Bagnoli

What is the best set of strategies that can be undertaken to reduce the cost of treating an epidemic?The treatment of an epidemic outbreak requires many resources and has many associated social and economic costs. The measures necessary to prevent a disease into spiralling into a pandemic however are also very costly, both from the point of view of the individual considering them and the government that is subsidising or providing them. Human beings are likely to consider these costs when making decisions and thus they have a major impact on how people will act when face with an epidemic (they play a major role in human behaviour). In this work we intend to examine several strategies of containing an epidemic and an estimate of their associated costs.Notably, our model takes into account of varying awareness of indiviuals to the epidemic during its course as well as varying fatality. For all of the following the costs might be paid completely by the individuals or subsidised or completely paid for by the government.  
Virtual DRM Experiment 
Responsible: Elisa Guidi and Cristina Cecchini

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 FDC Experiment - (Five Degree of Complexity ) 
Responsible: Andrea Guazzini, Giorgio Gronchi, Alessandro Cini

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 Gamification Experiments
Responsible: Franco Bagnoli, Giorgio Gronchi, Andrea Guazzini                    

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