1,721,151 research outputs found
Generalized rich-club ordering in networks
No full textRich-club ordering refers to the tendency of nodes with a high degree to be more interconnected than expected. In this article, we consider the concept of rich-club ordering when generalized to structural measures that differ from the node degree and to non-structural measures (i.e. to node metadata). The differences in considering rich-club ordering with respect to both structural and non-structural measures is then discussed in terms of employed coefficients and of appropriate null models (link rewiring vs. metadata reshuffling). Once a framework for the evaluation of generalized rich-club ordering is defined, we investigate such a phenomenon in real networks provided with node metadata. By considering different notions of node richness, we compare structural and non-structural rich-club ordering, observing how external information about the network nodes is able to validate the presence of rich-clubs in networked systems
Ambiguity of network outcomes
No full textThe extent to which available data is continuously growing in terms of volume is forcing organizations to contend with and seek to resolve the so-called Big Data Challenge. Big data comes or can be structured in the form of networks from which information can be extracted via statistical and computational tools. The results of such investigations can be generally referred to as network outcomes. Such outcomes, despite being often characterized by a inner ambiguity, need to be well understood and interpreted in order to exploit the potentialities of network data, especially in practical situations. For this reason, addressing the ambiguity of network outcomes becomes a key issue in business-related environments, where the possibility of rapidly interpreting and properly exploiting network data can positively affect performances. In this paper, we propose a framework to face ambiguity of network outcomes that, by means of specific solutions, allows practitioners to successfully interpret and exploit the obtained outcomes
Correction to: Financial interbanking networks resilience under shocks propagation (Annals of Operations Research, (2022), 10.1007/s10479-022-04567-w)
No full textThis correction is published as author Roy Cerqueti overlooked to include his second affiliation during proofing and needs to be read as: School of Business, London South Bank University, UK. Original article has been corrected
Evaluating relevance and redundancy to quantify how binary node metadata interplay with the network structure
No full textNetworks are real systems modelled through mathematical objects made up of nodes and links arranged into peculiar and deliberate (or partially deliberate) topologies. Studying these real-world topologies allows for several properties of interest to be revealed. In real networks, nodes are also identified by a certain number of non-structural features or metadata. Given the current possibility of collecting massive quantity of such metadata, it becomes crucial to identify automatically which are the most relevant for the observed structure. We propose a new method that, independently from the network size, is able to not only report the relevance of binary node metadata, but also rank them. Such a method can be applied to networks from any domain, and we apply it in two heterogeneous cases: a temporal network of technology transfer and a protein-protein interaction network. Together with the relevance of node metadata, we investigate the redundancy of these metadata displaying by the results on a Redundancy-Relevance diagram, which is able to highlight the differences among vectors of metadata from both a structural and a non-structural point of view. The obtained results provide insights of a practical nature into the importance of the observed node metadata for the actual network structure
The interconnectedness of the economic content in the speeches of the US Presidents
Full text linkThe speeches stated by influential politicians can have a decisive impact on the future of a country. In particular, the economic content of such speeches affects the economy of countries and their financial markets. For this reason, we examine a novel dataset containing the economic content of 951 speeches stated by 45 US Presidents from George Washington (April 1789) to Donald Trump (February 2017). In doing so, we use an economic glossary carried out by means of text mining techniques. The goal of our study is to examine the structure of significant interconnections within a network obtained from the economic content of presidential speeches. In such a network, nodes are represented by talks and links by values of cosine similarity, the latter computed using the occurrences of the economic terms in the speeches. The resulting network displays a peculiar structure made up of a core (i.e. a set of highly central and densely connected nodes) and a periphery (i.e. a set of non-central and sparsely connected nodes). The presence of different economic dictionaries employed by the Presidents characterize the core-periphery structure. The Presidents' talks belonging to the network's core share the usage of generic (non-technical) economic locutions like "interest" or "trade". While the use of more technical and less frequent terms characterizes the periphery (e.g. "yield"). Furthermore, the speeches close in time share a common economic dictionary. These results together with the economics glossary usages during the US periods of boom and crisis provide unique insights on the economic content relationships among Presidents' speeches
Municipal waste management: A complex network approach with an application to Italy
No full textThe paper contributes to the debate concerning the management of municipal solid waste by providing an analysis of two key aspects of waste management - namely, waste separation and dispatch to treatment plants. Our analysis aims at detecting the extent to which actual behavior in (close-by) municipalities is similar with respect to those two aspects. To pursue our scope, a complex network approach is followed. In particular, we conceptualize, explore and compare two networks, whose nodes are the municipalities, while weights synthesize in one network the percentage of sorted waste that is collected at a municipal level, and in the other one the distance from the waste processing plants used by each municipality. The theoretical network models are implemented through an empirical study based on a high quality dataset referred to Italian municipalities. In this regard, the detection of communities of municipalities and their geospatial contextualization are introduced as devices for a complete description of current practices of municipal waste separation and transfers in Italy
Structural bounds on the dyadic effect
No full textThe dyadic effect is a phenomenon that occurs when the number of links between nodes sharing a common feature is larger than expected if the features are distributed randomly on the network. In this article, we consider the case when nodes are distinguished by a binary characteristic. Under these circumstances, two independent parameters, namely dyadicity and heterophilicity are able to detect the presence of the dyadic effect and to measure how much the considered characteristic affects the network topology. The distribution of nodes characteristics can be investigated within a two-dimensional space that represents the feasible region of the dyadic effect, which is bound by two upper bounds on dyadicity and heterophilicity. Using some network structural arguments, we are able to improve such upper bounds and introduce two new lower bounds, providing a reduction of the feasible region of the dyadic effect as well as constraining dyadicity and heterophilicity within a specific range. Some computational experiences show the bounds effectiveness and their usefulness with regards to different classes of networks
A ground track-based approach to design satellite constellations
No full textFollowing an approach based on ground track analysis, original and compact relationships which permit the construction of ground track patterns and the determination of satellite arrangements able to generate appropriate track distance and revisit frequency over a given area are presented. These equations are valid in the general case of elliptical orbit and can easily be implemented in computer codes devoted to the design of single and multi-plane satellite constellations
Connections matter: a proxy measure for evaluating network membership with an application to the Seventh Research Framework Programme
No full textAlthough the topic of networks has received significant attention from the scientific literature, it remains to be seen whether it is possible to quantify the degree to which an organisation benefits from being part of a network. Starting from the concept of network value and that of Metcalfe’s Law, this paper introduces and defines the collective network effect (CNE). CNE is based on the concept that a network member is not only affected by its friends but also by the friends of its friends. By taking into account network connection patterns, CNE provides a proxy for quantifying the benefit of network membership. We computed the CNE for the nodes of a large network built using the whole set of common projects among the participants of the 7th Framework Programme for Research and Technological Development of the European Commission. The obtained results show that nodes with a higher CNE have access to substantially more conspicuous fundings than nodes with a lower CNE. In general, such a measure could supplement other centrality measures and be useful for organisations and companies aiming to evaluate both their current situation and the potential partners they should link with in order to extract the highest benefits from network membership
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