Multilayer Networks Analysis And Visualization
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Multilayer Networks Analysis And Visualization
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Author : Manlio De Domenico
language : en
Publisher: Springer Nature
Release Date : 2022-03-31
Multilayer Networks Analysis And Visualization written by Manlio De Domenico and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-31 with Computers categories.
The adoption of multilayer analysis techniques is rapidly expanding across all areas of knowledge, from social sciences (the first facing the complexity of such structures, decades ago) to computer science, from biology to engineering. However, until now, no book has dealt exclusively with the analysis and visualization of multilayer networks. Multilayer Networks: Analysis and Visualization provides a guided introduction to one of the most complete computational frameworks, named muxViz, with introductory information about the underlying theoretical aspects and a focus on the analytical side. Dozens of analytical scripts and examples to use the muxViz library in practice, by means of the Graphical User Interface or by means of the R scripting language, are provided. In addition to researchers in the field of network science, as well as practitioners interested in network visualization and analysis, this book will appeal to researchers without strong technical or computer science background who want to learn how to use muxViz software, such as researchers from humanities, social science and biology: audiences which are targeted by case studies included in the book. Other interdisciplinary audiences include computer science, physics, neuroscience, genetics, urban transport and engineering, digital humanities, social and computational social science. Readers will learn how to use, in a very practical way (i.e., without focusing on theoretical aspects), the algorithms developed by the community and implemented in the free and open-source software muxViz. The data used in the book is available on a dedicated (open and free) site.
Visual Analysis Of Multilayer Networks
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Author : Fintan McGee
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2021-06-10
Visual Analysis Of Multilayer Networks written by Fintan McGee and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-10 with Computers categories.
This is an overview and structured analysis of contemporary multilayer network visualization. It surveys techniques as well as tools, tasks, and analytics from within application domains. It also identifies research opportunities and examines outstanding challenges along with potential solutions and future research directions for addressing them. Visual Analysis of Multilayer Networks is not only for visualization researchers, but for those who need to visualize multilayer networks in the domain of complex systems, as well as anyone solving problems within application domains. The emergence of multilayer networks as a concept from the field of complex systems provides many new opportunities for the visualization of network complexity, and has also raised many new exciting challenges. The multilayer network model recognizes that the complexity of relationships between entities in real-world systems is better embraced as several interdependent subsystems (or layers) rather than a simple graph approach. Despite only recently being formalized and defined, this model can be applied to problems in the domains of life sciences, sociology, digital humanities, and more. Within the domain of network visualization there already are many existing systems, which visualize data sets having many characteristics of multilayer networks, and many techniques, which are applicable to their visualization.
Multilayer Social Networks
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Author : Mark E. Dickison
language : en
Publisher: Cambridge University Press
Release Date : 2016-07-19
Multilayer Social Networks written by Mark E. Dickison and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-19 with Computers categories.
This book unifies and consolidates methods for analyzing multilayer networks arising from the social and physical sciences and computing.
Complex Networks And Their Applications Vii
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Author : Luca Maria Aiello
language : en
Publisher: Springer
Release Date : 2018-12-01
Complex Networks And Their Applications Vii written by Luca Maria Aiello and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-01 with Technology & Engineering categories.
This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory, together with a wealth of applications. It presents the peer-reviewed proceedings of the VII International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2018), which was held in Cambridge on December 11–13, 2018. The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure and network dynamics; diffusion, epidemics and spreading processes; and resilience and control; as well as all the main network applications, including social and political networks; networks in finance and economics; biological and neuroscience networks; and technological networks.
Analysis Of Complex Data Sets Using Multilayer Networks
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Author : Abhishek Santra
language : en
Publisher:
Release Date : 2020
Analysis Of Complex Data Sets Using Multilayer Networks written by Abhishek Santra and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Boolean matrices categories.
We are on the cusp of analyzing a variety of data being collected in every walk of life - social, biological, health-care, corporate, climate, to name a few. The datasets are becoming diverse and complex in addition to increased size. Some of the complexity comes from interacting entities that arise in diverse disciplines, such as epidemiology [1], marketing strategy [2], social sciences [3], cybersecurity [4] and drug design [5]. Data sets becoming diverse and complex entails search for appropriate models and concomitant analytical techniques that are also efficient. Our ability to analyze large, complex, and disparate data for a broad set of analysis objectives differentiates big data analytics from mining which is narrow in scope both from data and analysis perspective. For big data analytics, flexibility of analysis (different from scalability)is important. Efficiency is important due to large number of analysis needs. Elegantly modeling and efficiently analyzing these complex datasets to obtain actionable knowledge presents several challenges. Traditional approaches, such as using single graph (or a single layer network or monoplex) may not be sufficient or appropriate for modeling and computation flexibility. Recently, multilayer networks have been proposed as an alternative for modeling such data elegantly. In this thesis, we first discuss different types of multilayer networks - homogeneous, heterogeneous and hybrid - from a modeling perspective. The benefits of this modeling, in terms of ease, understanding, and usage, are highlighted. Although big data analysis has warranted many new data models, not much attention has been paid to their modeling from requirements. Going straight from application requirements to data model and analysis, especially for complex data sets, is likely to be difficult, error prone, and not extensible to say the least. Hence for data models used in big data analysis, such as Multilayer Networks, there is a need to algorithmically transform the requirements using a systematic modeling approach, such as EER (Enhanced Entity Relationship). Here, we start with application requirements of complex data sets including analysis objectives and show how the EER approach can be leveraged for modeling given data to generate the MLN model and appropriate analysis expressions on them. However, this model brings with it a new set of challenges - both algorithmically and efficiency-wise - for its analysis. Since there are not many algorithms available in the literature for the analysis of MLN as a whole, applying currently available techniques to a transformed version of MLN leads to loss of information in terms of structure and semantics. Our proposed approach is to develop an analysis framework without transforming the MLN model so structure and semantics can be easily preserved. The general framework proposed and developed in this thesis is termed network decoupling. This framework is intended to be beneficial to all aggregate computations although this thesis focuses on two of them. The essence of this approach is to analyze each network layer individually and then use a composition function for aggregating individual layer results. This thesis demonstrates the network decoupling approach and its merits for widely-used graph aggregation analysis, such as community and centrality. For both community and centrality detection of MLN using Boolean operators, efficient composition functions and algorithms have been developed and validated for Homogeneous Multilayer Networks. To demonstrate its effectiveness, this thesis has proposed a new community definition of heterogeneous MLNs using the same framework. This not only uses the decoupling approach based on bipartite graph matching, but also preserves structure and semantics. Structure and semantics preservation for MLNs (both homogeneous and heterogeneous) is crucial for drill down analysis to clearly understand and interpret results. Our definition supports a family of community detection algorithms for heterogeneous MLNs which is very useful for matching analysis objectives. Further, for a broader analysis, we introduce several weight metrics for bringing in individual layer community characteristics on the MLN community. Essentially, this results in an extensible family of community computations. Finally, the framework and the algorithms proposed have been applied to real world (Internet Movie Database - IMDb, Database Bibliography - DBLP, UK Accidents, US Airlines, Facebook) and synthetic data sets in order to validate the approach, flexibility afforded, accuracy limits, and efficiency aspects. Meticulous drill down analysis on the final results has been carried out to come up with few surprising analysis results that predicted future potential events that we could verify by independently available ground truth. Based on this work, a dashboard for visualizing MLN analysis is underway.
Multiplex Networks
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Author : Emanuele Cozzo
language : en
Publisher: Springer
Release Date : 2018-06-27
Multiplex Networks written by Emanuele Cozzo and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-27 with Science categories.
This book provides the basis of a formal language and explores its possibilities in the characterization of multiplex networks. Armed with the formalism developed, the authors define structural metrics for multiplex networks. A methodology to generalize monoplex structural metrics to multiplex networks is also presented so that the reader will be able to generalize other metrics of interest in a systematic way. Therefore, this book will serve as a guide for the theoretical development of new multiplex metrics. Furthermore, this Brief describes the spectral properties of these networks in relation to concepts from algebraic graph theory and the theory of matrix polynomials. The text is rounded off by analyzing the different structural transitions present in multiplex systems as well as by a brief overview of some representative dynamical processes. Multiplex Networks will appeal to students, researchers, and professionals within the fields of network science, graph theory, and data science.
Multilayer Network Science
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Author : Oriol Artime
language : en
Publisher: Cambridge University Press
Release Date : 2022-09-30
Multilayer Network Science written by Oriol Artime and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-30 with Science categories.
Networks are convenient mathematical models to represent the structure of complex systems, from cells to societies. In the last decade, multilayer network science – the branch of the field dealing with units interacting in multiple distinct ways, simultaneously – was demonstrated to be an effective modeling and analytical framework for a wide spectrum of empirical systems, from biopolymers networks (such as interactome and metabolomes) to neuronal networks (such as connectomes), from social networks to urban and transportation networks. In this Element, a decade after one of the most seminal papers on this topic, the authors review the most salient features of multilayer network science, covering both theoretical aspects and direct applications to real-world coupled/interdependent systems, from the point of view of multilayer structure, dynamics and function. The authors discuss potential frontiers for this topic and the corresponding challenges in the field for the next future.
Visual Analysis Of Multilayer Networks
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Author : Fintan McGee
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
Visual Analysis Of Multilayer Networks written by Fintan McGee and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Mathematics categories.
The emergence of multilayer networks as a concept from the field of complex systems provides many new opportunities for the visualization of network complexity, and has also raised many new exciting challenges. The multilayer network model recognizes that the complexity of relationships between entities in real-world systems is better embraced as several interdependent subsystems (or layers) rather than a simple graph approach. Despite only recently being formalized and defined, this model can be applied to problems in the domains of life sciences, sociology, digital humanities, and more. Within the domain of network visualization there already are many existing systems, which visualize data sets having many characteristics of multilayer networks, and many techniques, which are applicable to their visualization. In this Synthesis Lecture, we provide an overview and structured analysis of contemporary multilayer network visualization. This is not only for researchers in visualization, but also for those who aim to visualize multilayer networks in the domain of complex systems, as well as those solving problems within application domains. We have explored the visualization literature to survey visualization techniques suitable for multilayer network visualization, as well as tools, tasks, and analytic techniques from within application domains. We also identify the research opportunities and examine outstanding challenges for multilayer network visualization along with potential solutions and future research directions for addressing them.
Business And Consumer Analytics New Ideas
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Author : Pablo Moscato
language : en
Publisher: Springer
Release Date : 2019-05-30
Business And Consumer Analytics New Ideas written by Pablo Moscato and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-30 with Computers categories.
This two-volume handbook presents a collection of novel methodologies with applications and illustrative examples in the areas of data-driven computational social sciences. Throughout this handbook, the focus is kept specifically on business and consumer-oriented applications with interesting sections ranging from clustering and network analysis, meta-analytics, memetic algorithms, machine learning, recommender systems methodologies, parallel pattern mining and data mining to specific applications in market segmentation, travel, fashion or entertainment analytics. A must-read for anyone in data-analytics, marketing, behavior modelling and computational social science, interested in the latest applications of new computer science methodologies. The chapters are contributed by leading experts in the associated fields.The chapters cover technical aspects at different levels, some of which are introductory and could be used for teaching. Some chapters aim at building a common understanding of the methodologies and recent application areas including the introduction of new theoretical results in the complexity of core problems. Business and marketing professionals may use the book to familiarize themselves with some important foundations of data science. The work is a good starting point to establish an open dialogue of communication between professionals and researchers from different fields. Together, the two volumes present a number of different new directions in Business and Customer Analytics with an emphasis in personalization of services, the development of new mathematical models and new algorithms, heuristics and metaheuristics applied to the challenging problems in the field. Sections of the book have introductory material to more specific and advanced themes in some of the chapters, allowing the volumes to be used as an advanced textbook. Clustering, Proximity Graphs, Pattern Mining, Frequent Itemset Mining, Feature Engineering, Network and Community Detection, Network-based Recommending Systems and Visualization, are some of the topics in the first volume. Techniques on Memetic Algorithms and their applications to Business Analytics and Data Science are surveyed in the second volume; applications in Team Orienteering, Competitive Facility-location, and Visualization of Products and Consumers are also discussed. The second volume also includes an introduction to Meta-Analytics, and to the application areas of Fashion and Travel Analytics. Overall, the two-volume set helps to describe some fundamentals, acts as a bridge between different disciplines, and presents important results in a rapidly moving field combining powerful optimization techniques allied to new mathematical models critical for personalization of services. Academics and professionals working in the area of business anyalytics, data science, operations research and marketing will find this handbook valuable as a reference. Students studying these fields will find this handbook useful and helpful as a secondary textbook.
New Statistical Developments In Data Science
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Author : Alessandra Petrucci
language : en
Publisher: Springer Nature
Release Date : 2019-08-20
New Statistical Developments In Data Science written by Alessandra Petrucci and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-08-20 with Computers categories.
This volume collects the extended versions of papers presented at the SIS Conference “Statistics and Data Science: new challenges, new generations”, held in Florence, Italy on June 28-30, 2017. Highlighting the central role of statistics and data analysis methods in the era of Data Science, the contributions offer an essential overview of the latest developments in various areas of statistics research. The 35 contributions have been divided into six parts, each of which focuses on a core area contributing to “Data Science”. The book covers topics including strong statistical methodologies, Bayesian approaches, applications in population and social studies, studies in economics and finance, techniques of sample design and mathematical statistics. Though the book is mainly intended for researchers interested in the latest frontiers of Statistics and Data Analysis, it also offers valuable supplementary material for students of the disciplines dealt with here. Lastly, it will help Statisticians and Data Scientists recognize their counterparts’ fundamental role.
