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In this paper we present an analysis of the behavior of Italian Twitter users during national political elections. We monitor the volumes of the tweets related to the leaders of the various political parties and we compare them to the elections results. Furthermore, we study the topics that are associated with the co-occurrence of two politicians in the same tweet. We cannot conclude, from a simple statistical analysis of tweet volume and their time evolution, that it is possible to precisely predict the election outcome (or at least not in our case of study that was characterized by a “too-close-to-call” scenario). On the other hand, we found that the volume of tweets and their change in time provide a very good proxy of the final results. We present this analysis both at a national level and at smaller levels, ranging from the regions composing the country to macro-areas (North, Center, South). [ABSTRACT FROM AUTHOR]

The article discusses a study on the spatial properties and accessibility indicators of the commuter systems through Complex Network Analysis (CNA) in the municipality of Sardinia, Italy. It says that the origin-destination table (ODT) model was used to describe the daily movements of the commuters. The study reveals the strong connections of the geographical properties and the traffic properties of the system or the flow of the commuters.

The aim of this paper is to study the dynamics of the commuting system of two insular regions of Italy, Sardinia and Sicily, inspected as complex networks. The authors refer to a 20-year time period and take into account three census data sets about the work and study-driven inter-municipal origin-destination movements of residential inhabitants in 1981, 1991 and 2001. Since it is likely that the number of municipalities (in this case, the vertices of the system) does not display sharp variations, the authors direct the study to the variation of the properties emerging through both a topological and a weighted network representation of commuting in the time periods indicated. [ABSTRACT FROM AUTHOR]

We study the structure of the network representing the interurban commuting traffic of the Sardinia region, Italy, which amounts to 375 municipalities and 1 600 000 inhabitants. We use a weighted network representation in which vertices correspond to towns and the edges correspond to the actual commuting flows among those towns. We characterize quantitatively both the topological and weighted properties of the resulting network. Interestingly, the statistical properties of the commuting traffic exhibit complex features and nontrivial relations with the underlying topology. We characterize quantitatively the traffic backbone among large cities and we give evidence for a very high heterogeneity of the commuter flows around large cities. We also discuss the interplay between the topological and dynamical properties of the network as well as their relation with sociodemographic variables such as population and monthly income. This analysis may be useful at various stages in environmental planning and provides analytical tools for a wide spectrum of applications ranging from impact evaluation to decision making and planning support. [ABSTRACT FROM AUTHOR]

We analyze the network of relations between parliament members according to their voting behavior. In particular, we examine the emergent community structure with respect to political coalitions and government alliances. We rely on tools developed in the Complex Network literature to explore the core of these communities and use their topological features to develop new metrics for party polarization, internal coalition cohesiveness and government strength. As a case study, we focus on the Chamber of Deputies of the Italian Parliament, for which we are able to characterize the heterogeneity of the ruling coalition as well as parties specific contributions to the stability of the government over time. We find sharp contrast in the political debate which surprisingly does not imply a relevant structure based on established parties. We take a closer look to changes in the community structure after parties split up and their effect on the position of single deputies within communities. Finally, we introduce a way to track the stability of the government coalition over time that is able to discern the contribution of each member along with the impact of its possible defection. While our case study relies on the Italian parliament, whose relevance has come into the international spotlight in the present economic downturn, the methods developed here are entirely general and can therefore be applied to a multitude of other scenarios.

The analysis of organizational structures of healthcare organizations such as University teaching hospitals is a fundamental step toward improving health care services and making more efficient use of available resources. In this study, discharge abstract data from the University of Cagliari teaching hospital was analysed by using techniques borrowed from the theory of complex networks. A bipartite network was constructed by linking the physician and diagnosis fields of the discharge abstract data. The unipartite projection network was then constructed by quantifying the number of diagnoses the connected physicians had in common in one year. Community detection algorithms were then used to identify the 'best' community structure (i.e. organizational subdivisions) for the hospital organization. The identified community structure could lead to improved efficiency with respect to existing departmental divisions. Results show how the theory of complex networks can be a very powerful data mining tool with very promising implications for research in the fields of health care organizations and social networks.