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Mathematics
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New Advances in Social Networks Analysis
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New Advances in Social Networks Analysis

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E: Applied Mathematics".

Deadline for manuscript submissions: closed (20 November 2024) | Viewed by 2847

Special Issue Editors

Dr. Suhail M. Odeh

E-Mail Website
Guest Editor
Software Engineering Department, Bethlehem University, Bethlehem 18015, Palestine
Interests: wireless sensors network WSN; Internet of Things IoT; artificial intelligence; pattern recognition; intelligent systems; brain computer interface; multiagent system; data analysis and mining
Prof. Dr. Antonio Mora

E-Mail Website
Guest Editor
Department of Signal Theory, Telematics and Communications, University of Granada, 18071 Granada, Spain
Interests: artificial intelligence; games; ant colony; optimization; self-organizing maps

Special Issue Information

Dear Colleagues,

Currently, social networks play a major role in our lives, and many people depend on these networks for connection and communication. A huge number of people are connected to social networks, and there has been a significant increase in information. Globally, many researchers are involved in the application of data mining and machine learning algorithms to analyse the information gained through social networks. This Special Issue of  Mathematics, ‘New Advances in Social Networks Analysis’, provides an opportunity for researchers from around the world to introduce their work across aspects of social network analysis, including management, privacy, security, and advanced algorithms that analyse big data gathered from social networks.

The topic is open in the field of Social Network Analysis, and the journal seeks novel contributions that help mitigate possible challenges.

Dr. Suhail M. Odeh
Prof. Dr. Antonio Mora
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 submissions that pass pre-check are 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. Mathematics is an international peer-reviewed open access semimonthly 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 2600 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.

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

32 pages, 727 KiB  
Article
Effectiveness of Centrality Measures for Competitive Influence Diffusion in Social Networks
by Fairouz Medjahed, Elisenda Molina and Juan Tejada
Mathematics 2025, 13(2), 292; https://doi.org/10.3390/math13020292 - 17 Jan 2025
Viewed by 751
Abstract
This paper investigates the effectiveness of centrality measures for the influence maximization problem in competitive social networks (SNs). We consider a framework, which we call “I-Game” (Influence Game), to conceptualize the adoption of competing products as a strategic game. Firms, as players, aim [...] Read more.
This paper investigates the effectiveness of centrality measures for the influence maximization problem in competitive social networks (SNs). We consider a framework, which we call “I-Game” (Influence Game), to conceptualize the adoption of competing products as a strategic game. Firms, as players, aim to maximize the adoption of their products, considering the possible rational choice of their competitors under a competitive diffusion model. They independently and simultaneously select their seeds (initial adopters) using an algorithm from a finite strategy space of algorithms. Since strategies may agree to select similar seeds, it is necessary to include an initial seed tie-breaking rule into the game model of the I-Game. We perform an empirical study in a two-player game under the competitive independent cascade model with three different seed-tie-breaking rules using four real-world SNs. The objective is to compare the performance of centrality-based strategies with some state-of-the-art algorithms used in the non-competitive influence maximization problem. The experimental results show that Nash equilibria vary according to the SN, seed-tie-breaking rules, and budgets. Moreover, they reveal that classical centrality measures outperform the most effective propagation-based algorithms in a competitive diffusion setting in three graphs. We attempt to explain these results by introducing a novel metric, the Early Influence Diffusion (EID) index, which measures the early influence diffusion of a strategy in a non-competitive setting. The EID index may be considered a valuable metric for predicting the effectiveness of a strategy in a competitive influence diffusion setting. Full article
(This article belongs to the Special Issue New Advances in Social Networks Analysis)
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21 pages, 4451 KiB  
Article
Assessment Model of Interactions Required in Design Teams in High-Rise Building Projects
by Rodrigo F. Herrera, Eduardo I. Galaz-Delgado, Edison Atencio, Felipe Muñoz-La Rivera and Tito Castillo
Mathematics 2023, 11(14), 3073; https://doi.org/10.3390/math11143073 - 12 Jul 2023
Cited by 1 | Viewed by 1351
Abstract
There is a lack of knowledge of the interactions required over time among the members of a building project design team. Without a specific target, it is impossible to identify gaps to propose improvement plans in the coordination and management of projects in [...] Read more.
There is a lack of knowledge of the interactions required over time among the members of a building project design team. Without a specific target, it is impossible to identify gaps to propose improvement plans in the coordination and management of projects in the early stages. Therefore, this study proposes a model of the required interaction among the members of a building project design team during the different phases of the design process. The research was divided into three stages: (1) design team interactions; (2) construction of ideal interaction networks and proposed evaluation model; and (3) pilot cases—evaluation and analysis. Through this study, eight ideal networks were constructed, four for each interaction (information flow, collaboration, and coordination) and one for each design phase. In addition, a series of metrics were proposed to evaluate the current state of a building project, which, together with the constructed model networks, allowed the development of an evaluation method for real projects. Finally, two pilot cases were used to exemplify the use of the proposed model tool. Full article
(This article belongs to the Special Issue New Advances in Social Networks Analysis)
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