Creating context for social influence processes in multiplex networks

2017 ◽  
Vol 5 (1) ◽  
pp. 1-29 ◽  
Author(s):  
J. ANTONIO RIVERO OSTOIC
Keyword(s):  
Social Influence ◽  
Network Structures ◽  
Community Network ◽  
Data Set ◽  
Multiplex Networks ◽  
Multiplex Network ◽  
Different Types ◽  
Mutual Communication ◽  
Formal Business

AbstractThis paper elaborates on two theories of social influence processes to multiplex network structures. First, cohesion influence is based on mutual communication made by different types of relations, and second comparison influence that is built on contrasting types of tie. While a system of bundles with a mutual character constitutes the setting for a multiplex network exposure measure within cohesion, comparison influence is defined algebraically through classes of actors in terms of a weakly balanced semiring structure that considers positive, negative, and also ambivalent types of tie. A case study with these approaches is made on an entrepreneurial community network with formal business relations, informal friendship ties, and perceived competition among the firms, and the methods are validated with the Sampson Monastery data set.

scholarly journals MultiVERSE: a multiplex and multiplex-heterogeneous network embedding approach

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Léo Pio-Lopez ◽  
Alberto Valdeolivas ◽  
Laurent Tichit ◽  
Élisabeth Remy ◽  
Anaïs Baudot
Keyword(s):  
Heterogeneous Networks ◽  
Heterogeneous Network ◽  
Link Prediction ◽  
Network Embedding ◽  
Multiplex Networks ◽  
Multiplex Network ◽  
Gene Associations ◽  
Different Types ◽  
Embedding Methods ◽  
Node Embeddings

AbstractNetwork embedding approaches are gaining momentum to analyse a large variety of networks. Indeed, these approaches have demonstrated their effectiveness in tasks such as community detection, node classification, and link prediction. However, very few network embedding methods have been specifically designed to handle multiplex networks, i.e. networks composed of different layers sharing the same set of nodes but having different types of edges. Moreover, to our knowledge, existing approaches cannot embed multiple nodes from multiplex-heterogeneous networks, i.e. networks composed of several multiplex networks containing both different types of nodes and edges. In this study, we propose MultiVERSE, an extension of the VERSE framework using Random Walks with Restart on Multiplex (RWR-M) and Multiplex-Heterogeneous (RWR-MH) networks. MultiVERSE is a fast and scalable method to learn node embeddings from multiplex and multiplex-heterogeneous networks. We evaluate MultiVERSE on several biological and social networks and demonstrate its performance. MultiVERSE indeed outperforms most of the other methods in the tasks of link prediction and network reconstruction for multiplex network embedding, and is also efficient in link prediction for multiplex-heterogeneous network embedding. Finally, we apply MultiVERSE to study rare disease-gene associations using link prediction and clustering. MultiVERSE is freely available on github at https://github.com/Lpiol/MultiVERSE.

scholarly journals Enhancing synchrony in multiplex network due to rewiring frequency

2019 ◽  
Vol 475 (2230) ◽  
pp. 20190460 ◽  
Author(s):  
Sarbendu Rakshit ◽  
Bidesh K. Bera ◽  
Jürgen Kurths ◽  
Dibakar Ghosh
Keyword(s):  
Numerical Simulations ◽  
Local Stability ◽  
Lorenz System ◽  
Stability Conditions ◽  
Network Architectures ◽  
Stability Function ◽  
Individual Layer ◽  
Multiplex Networks ◽  
Multiplex Network ◽  
Different Types

Most of the previous studies on synchrony in multiplex networks have been investigated using different types of intralayer network architectures which are either static or temporal. Effect of a temporal layer on intralayer synchrony in a multilayered network still remains elusive. In this paper, we discuss intralayer synchrony in a multiplex network consisting of static and temporal layers and how a temporal layer influences other static layers to enhance synchrony simultaneously. We analytically derive local stability conditions for intralayer synchrony based on the master stability function approach. The analytically derived results are illustrated by numerical simulations on up to five-layers multiplex networks with the paradigmatic Lorenz system as the node dynamics in each individual layer.

scholarly journals The Multiplex Dependency Structure of Financial Markets

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Nicolò Musmeci ◽  
Vincenzo Nicosia ◽  
Tomaso Aste ◽  
Tiziana Di Matteo ◽  
Vito Latora
Keyword(s):  
Financial Markets ◽  
Financial Time Series ◽  
Single Layer ◽  
Separate Analysis ◽  
Dependency Structure ◽  
Multiplex Networks ◽  
Multiplex Network ◽  
Different Types ◽  
Partial Correlations ◽  
Filtering Procedure

We propose here a multiplex network approach to investigate simultaneously different types of dependency in complex datasets. In particular, we consider multiplex networks made of four layers corresponding, respectively, to linear, nonlinear, tail, and partial correlations among a set of financial time series. We construct the sparse graph on each layer using a standard network filtering procedure, and we then analyse the structural properties of the obtained multiplex networks. The study of the time evolution of the multiplex constructed from financial data uncovers important changes in intrinsically multiplex properties of the network, and such changes are associated with periods of financial stress. We observe that some features are unique to the multiplex structure and would not be visible otherwise by the separate analysis of the single-layer networks corresponding to each dependency measure.

scholarly journals One hundred tweets from library land: A case study of RMIT University Library (academic library) and State Library of Victoria (public state library) in Australia

2018 ◽  
Vol 52 (1) ◽  
pp. 197-207
Author(s):  
Reham Ali Alsuhaibani
Keyword(s):  
Academic Library ◽  
Research Approach ◽  
User Engagement ◽  
Mixed Method Research ◽  
Data Set ◽  
University Library ◽  
Different Types ◽  
Twitter Account ◽  
State Library

Twitter is used by different library types to communicate and engage with their community. This case study focuses on content choices in tweets and the level of engagement generated, in the context of two different types of library. The current study attempts to examine the contents of Library Twitter account of two libraries (academic and public) with the aim of evaluating in a comparative mode, their themes and levels of user engagement. This research used a mixed method research approach. For quantitative approach, this study analyzed 100 Tweets from each library, i.e. RMIT University Library and State Library of Victoria. Also, the study analyzed a number of tweets and levels of engagement by recording numbers of likes, replies and retweets. The qualitative aspect analyzed each Tweet to determine engagement level and type of content shared by each library. The results demonstrate that the public and academic libraries publish different types of content. The varied nature, audience and mandate of each library appear to influence the focus of their tweets. Also, the results show that the level of engagement is a factor of the numbers of tweets in any theme. The limitation of this study is the data set contained only 100 tweets for each library. Moreover, the number of users and registered library accounts had probably increased since the study was conducted.

scholarly journals Multiplex Networks of the Guarantee Market: Evidence from China

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-7 ◽  
Author(s):  
Shouwei Li ◽  
Shihang Wen
Keyword(s):  
Betweenness Centrality ◽  
Single Layer ◽  
Eigenvector Centrality ◽  
Scale Free ◽  
Multiplex Networks ◽  
Multiplex Network ◽  
Different Types ◽  
Single Layer Network

We investigate a multiplex network of the guarantee market with three layers corresponding to different types of guarantee relationships in China. We find that three single-layer networks all have the scale-free property and are of disassortative nature. A single-layer network is not quite representative of another single-layer network. The result of the betweenness centrality shows that central companies in one layer are not necessarily central in another layer. And the eigenvector centrality has the same result of the betweenness centrality except the top central company.

scholarly journals Inverse Percolation to Quantify Robustness in Multiplex Networks

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Edwin Montes-Orozco ◽  
Roman-Anselmo Mora-Gutiérrez ◽  
Bibiana Obregón-Quintana ◽  
Sergio-G. de-los-Cobos-Silva ◽  
Eric A. Rincón-García ◽  
...  
Keyword(s):  
Mathematical Model ◽  
Social Networks ◽  
Single Layer ◽  
Multiplex Networks ◽  
Vertex Separator ◽  
Multiplex Network ◽  
The World ◽  
Structural Measure ◽  
The Mathematical Model

Inverse percolation is known as the problem of finding the minimum set of nodes whose elimination of their links causes the rupture of the network. Inverse percolation has been widely used in various studies of single-layer networks. However, the use and generalization of multiplex networks have been little considered. In this work, we propose a methodology based on inverse percolation to quantify the robustness of multiplex networks. Specifically, we present a modified version of the mathematical model for the multiplex-vertex separator problem (m-VSP). By solving the m-VSP, we can find nodes that cause the rupture of the mutually connected giant component (MCGC) and the large viable cluster (LVC) when their links are removed from the network. The methodology presented in this work was tested in a set of benchmark networks, and as case study, we present an analysis using a set of multiplex social networks modeled with information about the main characteristics of the best universities in the world and the universities in Mexico. The results show that the methodology presented in this work can work in different models and types of 2- and 3-layer multiplex networks without dividing the entire multiplex network into single-layer as some techniques described in the specific literature. Furthermore, thanks to the fact that the technique does not require the calculation of some structural measure or centrality metric, and it is easy to scale for networks of different sizes.

Participatory Mapping in Browns Canyon National Monument, Colorado (USA)

2017 ◽  
Vol 1 (1) ◽  
pp. 1-16
Author(s):  
John Harner ◽  
Lee Cerveny ◽  
Rebecca Gronewold
Keyword(s):  
Land Management ◽  
Planning Process ◽  
Management Plan ◽  
Bureau Of Land Management ◽  
National Monument ◽  
Resource Managers ◽  
Different Types ◽  
Us Forest Service ◽  
Natural Resource Managers

Natural resource managers need up-to-date information about how people interact with public lands and the meanings these places hold for use in planning and decision-making. This case study explains the use of public participatory Geographic Information System (GIS) to generate and analyze spatial patterns of the uses and values people hold for the Browns Canyon National Monument in Colorado. Participants drew on maps and answered questions at both live community meetings and online sessions to develop a series of maps showing detailed responses to different types of resource uses and landscape values. Results can be disaggregated by interaction types, different meaningful values, respondent characteristics, seasonality, or frequency of visit. The study was a test for the Bureau of Land Management and US Forest Service, who jointly manage the monument as they prepare their land management plan. If the information generated is as helpful throughout the entire planning process as initial responses seem, this protocol could become a component of the Bureau’s planning tool kit.

Comparative Analysis of Machine Learning Techniques Using Predictive Modeling

2020 ◽  
Vol 13 ◽  
Author(s):  
Ritu Khandelwal ◽  
Hemlata Goyal ◽  
Rajveer Singh Shekhawat
Keyword(s):  
Machine Learning ◽  
Comparative Analysis ◽  
Data Science ◽  
Training Data ◽  
Machine Learning Techniques ◽  
Future Trends ◽  
Data Set ◽  
Learning Stage ◽  
Learning Techniques ◽  
Different Types

Introduction: Machine learning is an intelligent technology that works as a bridge between businesses and data science. With the involvement of data science, the business goal focuses on findings to get valuable insights on available data. The large part of Indian Cinema is Bollywood which is a multi-million dollar industry. This paper attempts to predict whether the upcoming Bollywood Movie would be Blockbuster, Superhit, Hit, Average or Flop. For this Machine Learning techniques (classification and prediction) will be applied. To make classifier or prediction model first step is the learning stage in which we need to give the training data set to train the model by applying some technique or algorithm and after that different rules are generated which helps to make a model and predict future trends in different types of organizations. Methods: All the techniques related to classification and Prediction such as Support Vector Machine(SVM), Random Forest, Decision Tree, Naïve Bayes, Logistic Regression, Adaboost, and KNN will be applied and try to find out efficient and effective results. All these functionalities can be applied with GUI Based workflows available with various categories such as data, Visualize, Model, and Evaluate. Result: To make classifier or prediction model first step is learning stage in which we need to give the training data set to train the model by applying some technique or algorithm and after that different rules are generated which helps to make a model and predict future trends in different types of organizations Conclusion: This paper focuses on Comparative Analysis that would be performed based on different parameters such as Accuracy, Confusion Matrix to identify the best possible model for predicting the movie Success. By using Advertisement Propaganda, they can plan for the best time to release the movie according to the predicted success rate to gain higher benefits. Discussion: Data Mining is the process of discovering different patterns from large data sets and from that various relationships are also discovered to solve various problems that come in business and helps to predict the forthcoming trends. This Prediction can help Production Houses for Advertisement Propaganda and also they can plan their costs and by assuring these factors they can make the movie more profitable.

Effective Altruism

2019 ◽  
Keyword(s):  
Animal Welfare ◽  
Poverty Alleviation ◽  
Future Generations ◽  
Global Poverty ◽  
Global Community ◽  
Helping Others ◽  
The World ◽  
Different Types ◽  
Effective Altruism

The effective altruism movement consists of a growing global community of people who organize significant parts of their lives around two key ideas, represented in its name. Altruism: If we use a significant portion of the resources in our possession—whether money, time, or talents—with a view to helping others, we can improve the world considerably. Effectiveness: When we do put such resources to altruistic use, it is crucial to focus on how much good this or that intervention is reasonably expected to do per unit of resource expended (for example, per dollar donated). While global poverty is a widely used case study in introducing and motivating effective altruism, if the ultimate aim is to do the most good one can with the resources expended, it is far from obvious that global poverty alleviation is highest priority cause area. In addition to ranking possible poverty-alleviation interventions against one another, we can also try to rank interventions aimed at very different types of outcome against one another. This includes, for example, interventions focusing on animal welfare or future generations. The scale and organization of the effective altruism movement encourage careful dialogue on questions that have perhaps long been there, throwing them into new and sharper relief, and giving rise to previously unnoticed questions. In the present volume, the first of its kind, a group of internationally recognized philosophers, economists, and political theorists contribute in-depth explorations of issues that arise once one takes seriously the twin ideas of altruistic commitment and effectiveness.

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