Page 11 of 13
In this paper we study the problem of walk-specific information spread in directed complex social networks. Classical models usually analyze the “explosive” spread of information on social networks (e.g., Twit...
The advent of Online Social Networks (OSNs) has offered the opportunity to study the dynamics of information spread and influence propagation at a huge scale. Considerable research has focused on the social in...
Real network datasets provide significant benefits for understanding phenomena such as information diffusion or network evolution. Yet the privacy risks raised from sharing real graph datasets, even when strip...
We develop and test a rewiring method (originally proposed by Newman) which allows to build random networks having pre-assigned degree distribution and two-point correlations. For the case of scale-free degree...
We apply recent innovations in network science to analyze how correlations of stock returns evolve over time. To illustrate these techniques we study the returns of 30 industry stock portfolios from 1927 to 20...
We present a model for network transformation mediated by confinement, as a demonstration of a simple network dynamics that has a direct connection with real world quantities. The model has the capacity of gen...
This paper addresses two critical questions related to (1) the co-evolutionary dynamics between information diffusion and network topology and (2) the relationship between viral content and social reinforcemen...
Understanding traffic flow in urban areas has great importance and implications from an economic, social and environmental point of view. For this reason, numerous disciplines are working on this topic. Althou...
The conventional notion of community that favors a high ratio of internal edges to outbound edges becomes invalid when each vertex participates in multiple communities. Such a behavior is commonplace in social...
real-world networks such as social and communication networks are too large to be observed entirely. Such networks are often partially observed such that network size, network topology, and nodes of the original ...
Community detection has proved to be extremely successful in a variety of domains. However, most of the algorithms used in practice assume networks are unchanging in time. This assumption is violated for many ...
Networked power grid systems are susceptible to a phenomenon known as Coherent Swing Instability (CSI), in which a subset of machines in the grid lose synchrony with the rest of the network. We develop network...
We study how the community structure of bipartite mutualistic networks changes in a dynamic context. First, we consider a real mutualistic network and introduce extinction events according to several scenarios...
Transcriptional co-expression networks represent the concerted gene regulation programs by means of statistical inference of co-expression patterns. The rich phenomenology of transcriptional processes behind c...
In real world complex networks, communities are usually both overlapping and hierarchical. A very important class of complex networks is the bipartite networks. Maximal bicliques are the strongest possible str...
Knowledge graph will be usefull for the intelligent system. As the relationship prediction on the knowledge graph becomes accurate, construction of a knowledge graph and detection of erroneous information incl...
Social structures and interpersonal relationships may be represented as social networks consisting of nodes corresponding to people and links between pairs of nodes corresponding to relationships between those...
Dynamic networks are networks with temporal relationship features which evolve over time by the inclusion and deletion of nodes and edges. Suppressing the epidemic spreading in such networks is quite challengi...
We have investigated community structure in the co-inventor network of a given cohort of patents and related this structure to the dynamics of how these patents acquire their first citation. A statistically si...
A heterogeneous continuous time random walk is an analytical formalism for studying and modeling diffusion processes in heterogeneous structures on microscopic and macroscopic scales. In this paper we study bo...
Social networks often has the graph structure of giant strongly connected component (GSCC) and its upstream and downstream portions (IN and OUT), known as a bow-tie structure since a pioneering study on the Wo...
To properly capture the complexity of influence propagation phenomena in real-world contexts, such as those related to viral marketing and misinformation spread, information diffusion models should fulfill a n...
The use of networks to analyze biological data, such as large gene or protein expression datasets, is on the rise. Often, there is an interest of identifying modules (or communities) of biological molecules th...
Growing evidence shows that social media facilitate diffusion of both pro-recovery and anti-recovery information among people affected by mental health problems, while little is known about the associations of...
Companies face increased product complexity that involves reviewing and optimizing product development business processes.This leads to an increasingly multidisciplinary approach. Research units and multi-loca...
We deal with the problem of modeling and characterizing the community structure of complex systems. First, we propose a mathematical model for directed temporal networks based on the paradigm of activity drive...
As recent work demonstrated, the task of identifying communities in networks can be considered analogous to the classical problem of decoding messages transmitted along a noisy channel. We leverage this analog...
In this paper, we present an analysis of the emotion-exchange patterns that arise from Twitter messages sent during emergency events. To this end, we performed a systematic structural analysis of the multiplex...
In the early career phase of higher education, the social relationships with peers are a critical source of developmental support. Peer support relationships tend to be reciprocal and multiplex, such that the ...
We examine students’ representations of their conceptions of the interlinked nature of science history and general history, as well as cultural history. Such knowledge landscapes of the history of science are ...
The Correction to this article has been published in Applied Network Science 2020 5:42
This paper studies the driving forces behind the formation of ties within the major communities in the Japanese nationwide network of production, which contains one million firms and five million links between...
The growing availability of multirelational data gives rise to an opportunity for novel characterization of complex real-world relations, supporting the proliferation of diverse network models such as Attribut...
In this work, we investigate how court decisions aggregate citations in the European Court of Human Rights. Using the Bass model, we quantify the prevalence of the rich-get-richer phenomenon. We find that the ...
Electronic healthcare records contain large volumes of unstructured data in different forms. Free text constitutes a large portion of such data, yet this source of richly detailed information often remains und...
This paper describes a network reduction technique to reveal possibly hidden relational patterns in information diffusion networks of interlinked content published across different types of online media. Topic...
The fundamental understanding of altered complex molecular interactions in a diseased condition is the key to its cure. The overall functioning of these molecules is kind of jugglers play in the cell orchestra...
The success of a film is usually measured through its box-office revenue or through the opinion of professional critics; such measures, however, may be influenced by external factors, such as advertisement or ...
Over the last decades, both advanced and emerging economies have experienced a
Diabetes is a significant health concern with more than 30 million Americans living with diabetes. Onset of diabetes increases the risk for various complications, including kidney disease, myocardial infractio...
Based on the statistical features, short text messages published by different gender users are different in terms of the words and semantics used. In this paper, two new features are constructed after construc...
Tools from network science can be utilized to study relations between diseases. Different studies focus on different types of inter-disease linkages. One of them is the comorbidity patterns derived from large-...
Understanding the relationship between individuals’ social networks and health could help devise public health interventions for reducing incidence of unhealthy behaviors or increasing prevalence of healthy on...
Creating a map of actors and their leanings is important for policy makers and stakeholders in the European Commission’s ‘Better Regulation Agenda’. We explore publicly available information about the European...
Even though the heterogeneity of centrality in social networks is well documented, its role and effect on network stability in real life remains unclear. The literature roughly suggests that network structure ...
Ideas, information, viruses: all of them, with their mechanisms, spread over the complex social information, viruses: all tissues described by our interpersonal relations. Usually, to simulate and understand t...
An electroencephalography (EEG) coherence network is a representation of functional brain connectivity, and is constructed by calculating the coherence between pairs of electrode signals as a function of frequ...
The 2008 financial crisis unveiled the intrinsic failures of the financial system as we know it. As a consequence, impact investing started to receive increasing attention, as evidenced by the high market grow...
In corporate networks, firms are connected through links of corporate ownership and shared directors, connecting the control over major economic actors in our economies in meaningful and consequential ways. Most ...
With the growing ubiquity of data in network form, clustering in the context of a network, represented as a graph, has become increasingly important. Clustering is a very useful data exploratory machine learni...
In the last years complex networks tools contributed to provide insights on the structure of research, through the study of collaboration, citation and co-occurrence networks. The network approach focuses on p...
Citation Impact 2023
Journal Impact Factor: 1.3
5-year Journal Impact Factor: N/A
Source Normalized Impact per Paper (SNIP): 0.955
SCImago Journal Rank (SJR): 0.526
Speed 2023
Submission to first editorial decision (median days): 11
Submission to acceptance (median days): 119
Usage 2023
Downloads: 581,134
Altmetric mentions: 776
Abstract and indexing coverage
CNKI
dblp
DOAJ
EBSCO Academic Search
EBSCO Discovery Service
EBSCO STM Source
EBSCO TOC Premier
ESCI
Google Scholar
Inspec
OCLC
ProQuest - Summon
Scopus
Visit the membership page to check if your institution is a member and learn how you could save on article-processing charges (APCs).
