scholarly journals Complex Neutrosophic Hypergraphs: New Social Network Models

Algorithms ◽  
2019 ◽  
Vol 12 (11) ◽  
pp. 234 ◽  
Author(s):  
Anam Luqman ◽  
Muhammad Akram ◽  
Florentin Smarandache
Keyword(s):  
Social Networks ◽  
Sustainable Development ◽  
Social Network ◽  
Complex Systems ◽  
Network Models ◽  
Neutrosophic Set ◽  
Neutrosophic Sets ◽  
Score Functions ◽  
Proposed Model ◽  
Complex Valued

A complex neutrosophic set is a useful model to handle indeterminate situations with a periodic nature. This is characterized by truth, indeterminacy, and falsity degrees which are the combination of real-valued amplitude terms and complex-valued phase terms. Hypergraphs are objects that enable us to dig out invisible connections between the underlying structures of complex systems such as those leading to sustainable development. In this paper, we apply the most fruitful concept of complex neutrosophic sets to theory of hypergraphs. We define complex neutrosophic hypergraphs and discuss their certain properties including lower truncation, upper truncation, and transition levels. Furthermore, we define T-related complex neutrosophic hypergraphs and properties of minimal transversals of complex neutrosophic hypergraphs. Finally, we represent the modeling of certain social networks with intersecting communities through the score functions and choice values of complex neutrosophic hypergraphs. We also give a brief comparison of our proposed model with other existing models.

Certain models of granular computing based on rough fuzzy approximations

2020 ◽  
Vol 39 (3) ◽  
pp. 2797-2816
Author(s):  
Muhammad Akram ◽  
Anam Luqman ◽  
Ahmad N. Al-Kenani
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Problem Solving ◽  
Granular Computing ◽  
Research Study ◽  
Network Models ◽  
Mathematical Framework ◽  
Human Reasoning ◽  
Accuracy Measures ◽  
Lower And Upper Approximations

An extraction of granular structures using graphs is a powerful mathematical framework in human reasoning and problem solving. The visual representation of a graph and the merits of multilevel or multiview of granular structures suggest the more effective and advantageous techniques of problem solving. In this research study, we apply the combinative theories of rough fuzzy sets and rough fuzzy digraphs to extract granular structures. We discuss the accuracy measures of rough fuzzy approximations and measure the distance between lower and upper approximations. Moreover, we consider the adjacency matrix of a rough fuzzy digraph as an information table and determine certain indiscernible relations. We also discuss some general geometric properties of these indiscernible relations. Further, we discuss the granulation of certain social network models using rough fuzzy digraphs. Finally, we develop and implement some algorithms of our proposed models to granulate these social networks.

Knowledge Discovery from Online Communities

Data Mining ◽  
2013 ◽  
pp. 1230-1252
Author(s):  
Luca Cagliero ◽  
Alessandro Fiori
Keyword(s):  
Data Mining ◽  
Social Networks ◽  
Social Network ◽  
User Behavior ◽  
Network Models ◽  
Social Model ◽  
User Generated Content ◽  
Growth Trend ◽  
User Behaviors ◽  
Application Systems

This chapter presents an overview of social network features such as user behavior, social models, and user-generated content to highlight the most notable research trends and application systems built over such appealing models and online media data. It first describes the most popular social networks by analyzing the growth trend, the user behaviors, the evolution of social groups and models, and the most relevant types of data continuously generated and updated by the users. Next, the most recent and valuable applications of data mining techniques to social network models and user-generated content are presented. Discussed works address both social model extractions tailored to semantic knowledge inference and automatic understanding of the user-generated content. Finally, prospects of data mining research on social networks are provided as well.

Modification of host social networks by manipulative parasites

Behaviour ◽  
2018 ◽  
Vol 155 (7-9) ◽  
pp. 671-688 ◽  
Author(s):  
Robert Poulin
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Mating Behaviour ◽  
Group Formation ◽  
Network Models ◽  
Parasite Transmission ◽  
Activity Levels ◽  
Parasite Infections ◽  
Experimental Approaches ◽  
Host Behaviour

Abstract Social network models provide a powerful tool to estimate infection risk for individual hosts and track parasite transmission through host populations. Here, bringing together concepts from social network theory, animal personality, and parasite manipulation of host behaviour, I argue that not only are social networks shaping parasite transmission, but parasites in turn shape social networks through their effects on the behaviour of infected individuals. Firstly, I review five general categories of behaviour (mating behaviour, aggressiveness, activity levels, spatial distribution, and group formation) that are closely tied to social networks, and provide evidence that parasites can affect all of them. Secondly, I describe scenarios in which behaviour-altering parasites can modify either the role or position of individual hosts within their social network, or various structural properties (e.g., connectance, modularity) of the entire network. Experimental approaches allowing comparisons of social networks pre- versus post-infection are a promising avenue to explore the feedback loop between social networks and parasite infections.

scholarly journals Marketing and social networks: a criterion for detecting opinion leaders

2017 ◽  
Vol 26 (3) ◽  
pp. 347-366 ◽  
Author(s):  
Arnaldo Mario Litterio ◽  
Esteban Alberto Nantes ◽  
Juan Manuel Larrosa ◽  
Liliana Julia Gómez
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Online Social Networks ◽  
Semantic Analysis ◽  
Point Of View ◽  
Eigenvector Centrality ◽  
Content Type ◽  
Sporting Event ◽  
Centrality Metrics ◽  
Proposed Model

Purpose The purpose of this paper is to use the practical application of tools provided by social network theory for the detection of potential influencers from the point of view of marketing within online communities. It proposes a method to detect significant actors based on centrality metrics. Design/methodology/approach A matrix is proposed for the classification of the individuals that integrate a social network based on the combination of eigenvector centrality and betweenness centrality. The model is tested on a Facebook fan page for a sporting event. NodeXL is used to extract and analyze information. Semantic analysis and agent-based simulation are used to test the model. Findings The proposed model is effective in detecting actors with the potential to efficiently spread a message in relation to the rest of the community, which is achieved from their position within the network. Social network analysis (SNA) and the proposed model, in particular, are useful to detect subgroups of components with particular characteristics that are not evident from other analysis methods. Originality/value This paper approaches the application of SNA to online social communities from an empirical and experimental perspective. Its originality lies in combining information from two individual metrics to understand the phenomenon of influence. Online social networks are gaining relevance and the literature that exists in relation to this subject is still fragmented and incipient. This paper contributes to a better understanding of this phenomenon of networks and the development of better tools to manage it through the proposal of a novel method.

scholarly journals Image Based Classification of Rumor Information from the Social Network Platform

2021 ◽  
Vol 38 (5) ◽  
pp. 1413-1421
Author(s):  
Vallamchetty Sreenivasulu ◽  
Mohammed Abdul Wajeed
Keyword(s):  
Social Networks ◽  
Social Network ◽  
End Users ◽  
Web Based ◽  
Suggested Approach ◽  
Text Input ◽  
Social Network Data ◽  
Proposed Model ◽  
Spam Filters ◽  
Network Platform

Spam emails based on images readily evade text-based spam email filters. More and more spammers are adopting the technology. The essence of email is necessary in order to recognize image content. Web-based social networking is a method of communication between the information owner and end users for online exchanges that use social network data in the form of images and text. Nowadays, information is passed on to users in shorter time using social networks, and the spread of fraudulent material on social networks has become a major issue. It is critical to assess and decide which features the filters require to combat spammers. Spammers also insert text into photographs, causing text filters to fail. The detection of visual garbage material has become a hotspot study on spam filters on the Internet. The suggested approach includes a supplementary detection engine that uses visuals as well as text input. This paper proposed a system for the assessment of information, the detection of information on fraud-based mails and the avoidance of distribution to end users for the purpose of enhancing data protection and preventing safety problems. The proposed model utilizes Machine Learning and Convolutional Neural Network (CNN) methods to recognize and prevent fraud information being transmitted to end users.

scholarly journals Network Goal Analysis of Social and Organizational Systems: Testing Dynamic Network Theory in Complex Social Networks

2019 ◽  
Vol 56 (1) ◽  
pp. 107-129
Author(s):  
James D. Westaby ◽  
Adam K. Parr
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Complex Systems ◽  
Network Theory ◽  
Betweenness Centrality ◽  
Dynamic Network ◽  
Quadratic Assignment ◽  
Organizational Systems ◽  
Goal Striving ◽  
Shared Goal

Grounded in dynamic network theory, this study examined network goal analysis (NGA) to understand complex systems. NGA provides new insights by inserting goal nodes into social networks. Goal nodes can also represent missions, objectives, or desires, thus having wide applicability. The theory ties social networks to goal nodes through a parsimonious set of social network role linkages, such as independent goal striving, system supporting, feedback, goal preventing, supportive resisting, and system negating (i.e., those who are upset with others in the pursuit). Moreover, we extend the theory’s system reactance role linkage to better account for constructive conflicts. Two complex systems were examined: a team’s mission and an individual’s work project. In support of dynamic network theory, using the Quadratic Assignment Procedure, results demonstrated significant shared goal striving, system supporting, and shared connections between goal striving and system supporting. These findings manifest what we coin as multipendence: Systems having some actions independently involved with goals, while others are dependently involved in the associated network. NGA also demonstrated that the goal nodes manifested strong betweenness centrality, indicating that goal striving and feedback links were connecting entities across the wider system. Strategies to plan network goal interventions are illustrated with implications for practice.

scholarly journals A Novel Dynamic Multi-Criteria Decision Making Method Based on Generalized Dynamic Interval-Valued Neutrosophic Set

Symmetry ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 618 ◽  
Author(s):  
Nguyen Tho Thong ◽  
Florentin Smarandache ◽  
Nguyen Dinh Hoa ◽  
Le Hoang Son ◽  
Luong Thi Hong Lan ◽  
...  
Keyword(s):  
Decision Making ◽  
Evaluation Model ◽  
Real Life ◽  
Decision Makers ◽  
Neutrosophic Set ◽  
Multi Criteria Decision Making ◽  
Neutrosophic Sets ◽  
Proposed Model ◽  
Interval Valued ◽  
Knowledge Evaluation

Dynamic multi-criteria decision-making (DMCDM) models have many meaningful applications in real life in which solving indeterminacy of information in DMCDMs strengthens the potential application of DMCDM. This study introduces an extension of dynamic internal-valued neutrosophic sets namely generalized dynamic internal-valued neutrosophic sets. Based on this extension, we develop some operators and a TOPSIS method to deal with the change of both criteria, alternatives, and decision-makers by time. In addition, this study also applies the proposal model to a real application that facilitates ranking students according to attitude-skill-knowledge evaluation model. This application not only illustrates the correctness of the proposed model but also introduces its high potential appliance in the education domain.

Bridging Provider-Centric and User-Centric Social Networks

2012 ◽  
pp. 63-83 ◽  
Author(s):  
José C. Delgado
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Network Models ◽  
Migration Path ◽  
The Social ◽  
Active Service ◽  
Web Access ◽  
Close Cooperation ◽  
User Centric

Current social networks are centralized and driven by the providers’ formats, policies, and rules. Subscribing to several networks usually implies duplicating profile information and the effort of replicating changes when needed. Recently, there have been several proposals to support decentralized social networks, but these maintain the client-server paradigm. This chapter recognizes that the user is no longer a mere consumer, but rather a producer, and calls for a paradigm shift, with the user at the center of the social network scenarios, taking the role of an active service, in equal terms with social network providers. This leads to a unified user model: both individual and institutional entities are both users and providers and share the same protocols, although with different emphasis. We call this the user-centric approach and show a migration path from current social network models. To support this approach, we present a new Web access device, the browserver, which includes a browser and a server working in close cooperation, with the goal of replacing the classical browser but being backwards compatible with it to ease the migration path.

ANALYSIS OF COGNITIVE SOCIAL AND KNOWLEDGE NETWORKS FROM ELECTRONIC COMMUNICATION

2007 ◽  
Vol 01 (01) ◽  
pp. 87-120 ◽  
Author(s):  
NISHITH PATHAK ◽  
SANDEEP MANE ◽  
JAIDEEP SRIVASTAVA
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Electronic Communication ◽  
Knowledge Networks ◽  
Knowledge Network ◽  
Cognitive Network ◽  
Research Directions ◽  
Proposed Model ◽  
Cognitive Knowledge ◽  
New Research

This paper explains the classical social network analysis and discusses how computer networks effect a shift in constructing social networks. The paper then concentrates on analyzing cognitive aspects of a social network, explaining a simple but scalable approach for modeling a socio-cognitive network. Novel measures using such a socio-cognitive network model are defined and applications of such measures to extract useful information is illustrated on the Enron email dataset. The paper then describes a Dempster-Schafer theory based approach towards modeling a cognitive knowledge network and uses the Enron email dataset to illustrate how the proposed model can be used to capture actors' perceptions in a knowledge network. The paper concludes with a summary of the proposed models and a discussion on new research directions that can arise due to such cognitive analyses of electronic communication data.

scholarly journals Networks: A

2021 ◽  
pp. 71-92
Author(s):  
Jean Walrand
Keyword(s):  
Social Networks ◽  
Communication Network ◽  
Social Network ◽  
Queueing Networks ◽  
Classical Result ◽  
Network Models ◽  
Product Form ◽  
The Internet ◽  
Free Products ◽  
Exchange Information

AbstractSocial networks connect people and enable them to exchange information. News and rumors spread through these networks. We explore models of such propagations. The technology behind social networks is the internet where packets travel from queue to queue. We explain some key results about queueing networks.Section 5.1 explores a model of how rumors spread in a social network. Epidemiologists use similar models to study the spread of viruses. Section 5.2 explains the cascade of choices in a social network where one person’s choice is influenced by those of people she knows. Section 5.3 shows how seeding the market with advertising or free products affects adoptions. Section 5.4 studies a model of how media can influence the eventual consensus in a social network. Section 5.5 explores the randomness of the consensus in a group. Sections 5.6 and 5.7 present a different class of network models where customers queue for service. Section 5.6 studies a single queue and Sect. 5.7 analyzes a network of queues. Section 5.8 explains a classical optimization problem in a communication network: how to choose the capacities of different links. Section 5.9 discusses the suitability of queueing networks as models of the internet. Section 5.10 presents a classical result about a class of queueing networks known as product-form networks.

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