Search results for "work analysis"
showing 10 items of 232 documents
Network Centralities and Node Ranking
2017
An important problem in network analysis is understanding how much nodes are important in order to “propagate” the information across the input network. To this aim, many centrality measures have been proposed in the literature and our main goal here is that of providing an overview of the most important of them. In particular, we distinguish centrality measures based on walks computation from those based on shortest-paths computation. We also provide some examples in order to clarify how these measures can be calculated, with special attention to Degree Centrality, Closeness Centrality and Betweennes Centrality.
Statistically validated networks in bipartite complex systems.
2011
Many complex systems present an intrinsic bipartite nature and are often described and modeled in terms of networks [1-5]. Examples include movies and actors [1, 2, 4], authors and scientific papers [6-9], email accounts and emails [10], plants and animals that pollinate them [11, 12]. Bipartite networks are often very heterogeneous in the number of relationships that the elements of one set establish with the elements of the other set. When one constructs a projected network with nodes from only one set, the system heterogeneity makes it very difficult to identify preferential links between the elements. Here we introduce an unsupervised method to statistically validate each link of the pr…
Asymmetric Comparison and Querying of Biological Networks
2011
Comparing and querying the protein-protein interaction (PPI) networks of different organisms is important to infer knowledge about conservation across species. Known methods that perform these tasks operate symmetrically, i.e., they do not assign a distinct role to the input PPI networks. However, in most cases, the input networks are indeed distinguishable on the basis of how the corresponding organism is biologically well characterized. In this paper a new idea is developed, that is, to exploit differences in the characterization of organisms at hand in order to devise methods for comparing their PPI networks. We use the PPI network (called Master) of the best characterized organism as a …
Approximate Matching over Biological RDF Graphs
2012
In the last few years, the amount of biological interaction data discovered and stored in public databases (e.g., KEGG [2]) considerably increased. To this aim, RDF is a powerful representation for interactions (or pathways), since they can be modeled as directed graphs, often referred to as biological networks, where nodes represent cellular components and the (labeled or unlabeled) edges correspond to interactions among components. Often for a given organism some components are known to be linked by well studied interactions. Such groups of components are called modules and they can be represented by sub-graphs in the corresponding biological network model. At today, one of the most impor…
Correlation Analysis of Node and Edge Centrality Measures in Artificial Complex Networks
2021
The role of an actor in a social network is identified through a set of measures called centrality. Degree centrality, betweenness centrality, closeness centrality, and clustering coefficient are the most frequently used metrics to compute the node centrality. Their computational complexity in some cases makes unfeasible, when not practically impossible, their computations. For this reason, we focused on two alternative measures, WERW-Kpath and Game of Thieves, which are at the same time highly descriptive and computationally affordable. Our experiments show that a strong correlation exists between WERW-Kpath and Game of Thieves and the classical centrality measures. This may suggest the po…
Social network analysis: the use of graph distances to compare artificial and criminal networks
2021
Aim: Italian criminal groups become more and more dangerous spreading their activities into new sectors. A criminal group is made up of networks of hundreds of family gangs which extended their influence across the world, raking in billions from drug trafficking, extortion and money laundering. We focus in particular on the analysis of the social structure of two Sicilian crime families and we used a Social Network Analysis approach to study the social phenomena. Starting from a real criminal network extracted from meetings emerging from the police physical surveillance during 2000s, we here aim to create artificial models that present similar properties. Methods: We use specific tools of s…
A Relational Approach to Networks in a Tourism Destination: Business and Family Networks in San Vito Lo Capo, Sicily
2022
This article constructs a relational framework using the principles of the Network Approach to examining the business exchange structure of a tourist destination. Network Analysis is the methodology to analyse the metrics of collaboration and cooperation among destination companies. The model was applied in a remote tourist destination named San Vito Lo Capo on the island of Sicily, where tourism has significantly expanded in the last twenty years. The focus is on how groupings of small companies within family relations can govern and be responsible for tourism destination cooperation. As the main result, the existence was identified, of a relational framework where three clusters of famili…
Tourist destination network analysis: The ego network role
2017
This paper aims to analyse the different roles that enterprises have within a tourist destination by identifying the presence and possible role of leaders within the system. The Social Network Analysis (SNA) is a tool that offers a greater degree of understanding of the operation of the destination. The map of commercial relations between the leading players of tourist supply can provide greater insight into the main relations existing between enterprises and the principles that ensure and regulate operation. In keeping with this objective and building on the results of a previous paper (Iannolino and Ruggieri, 2012), the authors have focused their attention on the role of some enterprises …
Transnational Social Network Analysis
2012
AbstractThe following article discusses methods of social network analysis (SNA) as an approach in researching transnational social formations. SNA allows transnationality to be studied through relationships between actors, enabling the investigation of social structures which expand nation-state frameworks. Two empirical examples are used to address the central characteristics of the network analysis approach (focus on relations, systematic collection of data, means of visualising network data) and their relevance for research on cross-border social phenomena. The article also investigates the significance of geographical mobility in the research process, culminating in reflection on how “…
Transnational Social Networks—Current Perspectives
2012
“[T]here is something mysterious about social networks. We live surrounded by them, but usually cannot see more than one step beyond the people we are directly connected to, if that. It is like being stuck in a traffic jam surrounded by cars and trucks. The traffic helicopter can see beyond our immediate surroundings and suggest routes that might extricate us. Network analysis is like that helicopter. It allows us to see beyond our immediate circle.” (Kadushin, 2012: 4)