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Deterministic epidemic models, such as the Susceptible-Infected-Recovered (SIR) model, are immensely useful even if they lack the nuance and complexity of social contacts at the heart of network science modeli...
Random geometric graphs have become now a popular object of research. Defined rather simply, these graphs describe real networks much better than classical Erdős–Rényi graphs due to their ability to produce ti...
Initially emerged in the Chinese city Wuhan and subsequently spread almost worldwide causing a pandemic, the SARS-CoV-2 virus follows reasonably well the Susceptible–Infectious–Recovered (SIR) epidemic model o...
Providers of online marketplaces are constantly combatting against problematic transactions, such as selling illegal items and posting fictive items, exercised by some of their users. A typical approach to det...
Complex networks, such as transportation networks, social networks, or biological networks, capture the complex system they model by often representing only one type of interactions. In real world systems, the...
This paper introduces the strain elevation tension spring embedding (SETSe) algorithm. SETSe is a novel graph embedding method that uses a physical model to project feature-rich networks onto a manifold with s...
Drug development is a time-consuming process from the start of research to obtaining approval, and the probability of success with a candidate compound is extremely low. We aim to understand the characteristic...
The availability of effective test suites is critical for the development and maintenance of reliable software systems. To increase test effectiveness, software developers tend to employ larger and larger test...
This study models cross-national attitudes towards immigrants in East and Southeast Asia as a signed and weighted bipartite network of countries and evaluative reactions to a variety of political issues, or de...
Social media like Twitter or Instagram play the role of fertile platforms for self-exhibition and allow their users to earn a good repute. People higher in grandiosity share their contents in a charismatic way...
Think tanks have become central players in the political and policy ecosystem of the United States, yet the communication and coordination strategies and connections between them remain relatively unexamined. ...
The role of misinformation diffusion during a pandemic is crucial. An aspect that requires particular attention in the analysis of misinfodemics is the rationale of the source of false information, in particul...
We perform an extensive analysis of how sampling impacts the estimate of several relevant network measures. In particular, we focus on how a sampling strategy optimized to recover a particular spectral central...
In this study, we propose novel centrality measures considering multiple perspectives of nodes or node groups based on the facility location problem on a spatial network. The conventional centrality exclusivel...
The hypergraph-of-entity is a joint representation model for terms, entities and their relations, used as an indexing approach in entity-oriented search. In this work, we characterize the structure of the hype...
Social connections that reach distant places are advantageous for individuals, firms and cities, providing access to new skills and knowledge. However, systematic evidence on how firms build global knowledge a...
Topic modeling that can automatically assign topics to legal documents is very important in the domain of computational law. The relevance of the modeled topics strongly depends on the legal context they are u...
As illustrated by the 2008 global financial crisis, the financial distress of one country can trigger financial distress in other countries. We examine the problem of identifying such “systemically important” ...
We aim to explore the connections between structural network inequalities and bank’s customer spending behaviours, within an entire national ecosystem made of natural persons (i.e., an individual human being) ...
Human mobility connects urban dwellers and neighborhoods and impacts social equity. An in-depth understanding of human mobility helps to enhance urban resilience. However, limited research has focused on mobil...
Node connectivity plays a central role in temporal network analysis. We provide a broad study of various concepts of walks in temporal graphs, that is, graphs with fixed vertex sets but arc sets changing over ...
Computational and mathematical modelling towards understanding the structure and dynamics of biological systems has significantly impacted on translational neuroscience to face novel approaches toward neurolog...
Supply chains enable the flow of goods and services within economic systems. When mapped for the entire economy and geographic locations of a country, supply chains form a spatial web of interactions among sup...
Massive migrations have become increasingly prevalent over the last decades. A recent example is the Venezuelan migration crisis across South America, which particularly affects neighboring countries like Colo...
Resources such as FrameNet, which provide sets of semantic frame definitions and annotated textual data that maps into the evoked frames, are important for several NLP tasks. However, they are expensive to bui...
Worldwide urbanization calls for a deeper understanding of epidemic spreading within urban environments. Here, we tackle this problem through an agent-based model, in which agents move in a two-dimensional phy...
We present a model of worldwide crisis contagion based on the Google matrix analysis of the world trade network obtained from the UN Comtrade database. The fraction of bankrupted countries exhibits an on-off phas...
The COVID-19 pandemic has produced a flurry of online activity on social media sites. As such, analysis of social media data during the COVID-19 pandemic can produce unique insights into discussion topics and ...
Relationships in real systems are often not binary, but of a higher order, and therefore cannot be faithfully modelled by graphs, but rather need hypergraphs. In this work, we systematically develop formal too...
The Erasmus Program (EuRopean community Action Scheme for the Mobility of University Students), the most important student exchange program in the world, financed by the European Union and started in 1987, is ...
In recent history, the Panama Papers have comprised one of the largest and most influential leaks detailing information on offshore entities, company officers and financial (and legal) intermediaries, and has ...
Clustering is an essential technique for network analysis, with applications in a diverse range of fields. Although spectral clustering is a popular and effective method, it fails to consider higher-order stru...
Currently, the relation between edit behavior, link structure, and article quality is not well-understood in our community, notwithstanding that this relationship may facilitate editing processes and content q...
Studies of networked phenomena, such as interactions in online social media, often rely on incomplete data, either because these phenomena are partially observed, or because the data is too large or expensive ...
The daily exposure of social media users to propaganda and disinformation campaigns has reinvigorated the need to investigate the local and global patterns of diffusion of different (mis)information content on...
Complex networks are usually characterized by the presence of small and recurrent patterns of interactions between nodes, called network motifs. These small modules can help to elucidate the structure and the ...
The team formation problem has existed for many years in various guises. One important challenge in the team formation problem is to produce small teams that have a required set of skills. We propose a framewo...
A popular approach for understanding complex systems is a network analytic one: the system’s entities and their interactions are represented by a graph structure such that readily available methods suitable fo...
Attribute-aware community discovery aims to find well-connected communities that are also homogeneous w.r.t. the labels carried by the nodes. In this work, we address such a challenging task presenting Eva, an al...
The paper presents Intergraph, a graph-based visual analytics technical demonstrator for the exploration and study of content in historical document collections. The designed prototype is motivated by a practi...
Recent work has employed information theory in social and complex networks. Studies often discuss entropy in the degree distributions of a network. However, no specific work on entropy exists in clique network...
Learning on graphs is a subject of great interest due to the abundance of relational data from real-world systems. Many of these systems involve higher-order interactions (super-dyadic) rather than mere pairwi...
Community detection is one of the most important tasks in network analysis. It is increasingly clear that quality measures are not sufficient for assessing communities and structural properties play a key hole...
Software structure is the backbone for software systems. During the long time of software evolution, it is gradually weakened by continuous code modification and expansion driven by new requirements. Therefore...
Traffic is a challenge in rural and urban areas alike with negative effects ranging from congestion to air pollution. Ride-sharing poses an appealing alternative to personal cars, combining the traffic-reducin...
A problem that frequently occurs when mining complex networks is selecting algorithms with which to rank the relevance of nodes to metadata groups characterized by a small number of examples. The best algorith...
The study of co-expression programs in the context of cancer can help to elucidate the genetic mechanisms that are altered and lead to the disease. The identification of gene co-expression patterns, unique to ...
The position of a node in a social network, or node centrality, can be quantified in several ways. Traditionally, it can be defined by considering the local connectivity of a node (degree) and some non-local c...
Discovering the node roles in a network helps to solve diverse social problems. Role discovery attempts to predict the node roles from a network structure, and this method has been extensively studied in vario...
The determination of reliable early-warning indicators of economic crises is a hot topic in economic sciences. Pinning down recurring patterns or combinations of macroeconomic indicators is indispensable for a...
2022 Citation Impact
2.2 - 2-year Impact Factor
1.117 - SNIP (Source Normalized Impact per Paper)
0.603 - SJR (SCImago Journal Rank)
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