Special Issue "Role-Aware Analysis of Complex Networks"

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Multidisciplinary Applications".

Deadline for manuscript submissions: 28 February 2022.

Special Issue Editors

Dr. Gianni Costa
E-Mail Website
Guest Editor
Institute of High Performance Computing and Networks (ICAR) of the National Research Council of Italy (CNR), 87036 Rende, Italy
Interests: data mining; machine learning; recommender systems; social network analysis; text mining; semi-structured data analysis
Special Issues, Collections and Topics in MDPI journals
Dr. Riccardo Ortale
E-Mail Website
Guest Editor
Institute of High Performance Computing and Networks (ICAR) of the National Research Council of Italy (CNR), 87036 Rende, CS, Italy
Interests: data mining; machine learning; recommender systems; social network/media analysis; text mining; semistructured data analysis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Network analysis is a general and cross-disciplinary approach to scientific inquiry on complex systems such as, for example, human social systems, the World Wide Web, power grids, electronic circuits, communication networks, railways and food webs. Abstractly, complex systems can be conceptualized as wholes of components with mutual interactions. These are addressed from the network-centric perspective in the investigation of complex systems. Accordingly, the latter have been studied, understood and explained in terms of interactions among their components. Hitherto, various aspects of interest in the establishment of network interactions have been taken into account across several domains and applicative contexts. However, the incorporation of component roles in an effort to advance our comprehension of complex systems has yet to be fully valued.

The aim of this Special Issue is to promote an in-depth understanding of roles in complex network analysis. To this end, we call for novel insights into challenging issues, emerging trends as well as long studied problems and tasks, which have been formulated so far without a focus on roles. We solicit original contributions, including theoretical as well as application-oriented studies. In particular, we encourage the development of innovative models, methods, techniques and tools, which account for roles and additional aspects of interest in a seamlessly unified manner. Of particular interest are those interdisciplinary approaches that promote synergism among viewpoints, developments and advances within diverse areas. We also welcome original and comprehensive reviews of the literature on role-aware network analysis, with a focus on envisaging an appropriate exploitation of roles to revisit previous research, address new problems and identify unexplored directions. Extensions of previously published works are also invited, provided that at least 40% of new material is devoted to significant and unprecedented contributions, which must be clearly summarized in the introduction.

Dr. Gianni Costa
Dr. Riccardo Ortale
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Network roles: foundations, theory, representation, discovery and interpretation
  • Case studies and applications of networks roles
  • Role-aware analytics of large-scale complex networks
  • Role-aware community detection, anomaly discovery, link prediction and network completion
  • Role-aware information diffusion and cascading behavior
  • Roles in time-evolving and streaming networks
  • Roles in influence, reputation and trust networks
  • Roles in multi-layered and heterogeneous networks
  • Roles in viral marketing
  • Roles in uncertain networks
  • Role-aware social recommendation, user profiling and user behavior modeling
  • Roles in complex networks for community question-answering, IoT systems and physical infrastructures
  • Roles in network attacks, vulnerability, resilience, robustness and reconstruction
  • Roles in topic detection and tracking on networks
  • Role-aware network embedding
  • Role-aware visual representation of complex networks
  • Roles in covert networks
  • Roles in complex networks for mobility, healthcare, smart cities and smart grids
  • Role-aware modeling, analysis, mining and testing of complex networks in any other scientific or applicative domain

Published Papers (1 paper)

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Review

Review
Role-Aware Information Spread in Online Social Networks
Entropy 2021, 23(11), 1542; https://0-doi-org.brum.beds.ac.uk/10.3390/e23111542 - 19 Nov 2021
Viewed by 465
Abstract
Understanding the complex process of information spread in online social networks (OSNs) enables the efficient maximization/minimization of the spread of useful/harmful information. Users assume various roles based on their behaviors while engaging with information in these OSNs. Recent reviews on information spread in [...] Read more.
Understanding the complex process of information spread in online social networks (OSNs) enables the efficient maximization/minimization of the spread of useful/harmful information. Users assume various roles based on their behaviors while engaging with information in these OSNs. Recent reviews on information spread in OSNs have focused on algorithms and challenges for modeling the local node-to-node cascading paths of viral information. However, they neglected to analyze non-viral information with low reach size that can also spread globally beyond OSN edges (links) via non-neighbors through, for example, pushed information via content recommendation algorithms. Previous reviews have also not fully considered user roles in the spread of information. To address these gaps, we: (i) provide a comprehensive survey of the latest studies on role-aware information spread in OSNs, also addressing the different temporal spreading patterns of viral and non-viral information; (ii) survey modeling approaches that consider structural, non-structural, and hybrid features, and provide a taxonomy of these approaches; (iii) review software platforms for the analysis and visualization of role-aware information spread in OSNs; and (iv) describe how information spread models enable useful applications in OSNs such as detecting influential users. We conclude by highlighting future research directions for studying information spread in OSNs, accounting for dynamic user roles. Full article
(This article belongs to the Special Issue Role-Aware Analysis of Complex Networks)
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Role-aware Information Spread in Online Social Networks: A Review

Authors: Alon Bartal
Affiliation: The School of Business Administration, Bar-Ilan University, Israel

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