Computing secure sets in graphs using answer set programming

2015 ◽  
Vol 30 (4) ◽  
pp. 837-862 ◽  
Author(s):  
Michael Abseher ◽  
Bernhard Bliem ◽  
Günther Charwat ◽  
Frederico Dusberger ◽  
Stefan Woltran
Keyword(s):  
Graph Theory ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Answer Set Programming ◽  
Np Hard ◽  
Weighted Graphs ◽  
Answer Set

Abstract The notion of secure sets is a rather new concept in the area of graph theory. Applied to social network analysis, the goal is to identify groups of entities that can repel any attack or influence from the outside. In this article, we tackle this problem by utilizing Answer Set Programming (ASP). It is known that verifying whether a set is secure in a graph is already co-NP-hard. Therefore, the problem of enumerating all secure sets is challenging for ASP and its systems. In particular, encodings for this problem seem to require disjunction and also recursive aggregates. Here, we provide such encodings and analyse their performance using the Clingo system. Furthermore, we study several problem variants, including multiple secure or insecure sets, and weighted graphs.

scholarly journals Group Measures and Modeling for Social Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Vincent Levorato
Keyword(s):  
Complex System ◽  
Social Networks ◽  
Graph Theory ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Network Modeling ◽  
Complex Interactions ◽  
Social Network Modeling

Social network modeling is generally based on graph theory, which allows for study of dynamics and emerging phenomena. However, in terms of neighborhood, the graphs are not necessarily adapted to represent complex interactions, and the neighborhood of a group of vertices can be inferred from the neighborhoods of each vertex composing that group. In our study, we consider that a group has to be considered as a complex system where emerging phenomena can appear. In this paper, a formalism is proposed to resolve this problematic by modeling groups in social networks using pretopology as a generalization of the graph theory. After giving some definitions and examples of modeling, we show how some measures used in social network analysis (degree, betweenness, and closeness) can be also generalized to consider a group as a whole entity.

Emerging Forms of Collaboration

2016 ◽  
pp. 69-99
Author(s):  
Alexandra Antonopoulou ◽  
Eleanor Dare
Keyword(s):  
Graph Theory ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Community Of Practice ◽  
Motion Capture ◽  
Interaction Design ◽  
Collaborative Technologies ◽  
Custom Made ◽  
New Form

The chapter will outline the implications of two projects, namely the ‘Phi Books' (2008) and the ‘Digital Dreamhacker' (2011). These novel projects serve here as case studies for investigating new and challenging ways of advancing collaborative technologies, using in particular, Communities of Practice and insights gained from both embodiment and graph theory (social network analysis) as well as design. Both projects were developed collaboratively, between a computer programmer and a designer and a wider community of practice, consisting of other artists, writers, technologists and designers. The two systems that resulted also acted as methodologies, instigated by the authors with a view to facilitate, explore and comment on the act of collaboration. Both projects are multi-disciplinary, spanning ideas and techniques from mathematics and art, design and computer programming. The projects deploy custom-made software and fiction enmeshed structures, drawing upon methodologies that are embedded with dreams and stories while at the same time being informed by cutting-edge research into human behaviour and interaction design. The chapter will investigate how the projects deployed techniques and theoretical insights from social network analysis as well as motion capture technology and the wider concept of a Community of Practice, to extend and augment existing collaborative methods. The chapter draws upon Wenger et al (2002), as well as Siemens (2014) and Borgatti et al (2009), and will explore the idea of a new form of collective social and technological collaborative grammar, deploying gesture as well as Social Network Analysis. Moreover, the featured projects provide insights into the ways in which digital technology is changing society, and in turn, the important ways in which technology is embedded with the cultural and economic prerogatives of increasingly globalized cultures.

Structural Analysis With Graphs

2020 ◽  
pp. 31-47
Keyword(s):  
Social Networks ◽  
Graph Theory ◽  
Social Network ◽  
Social Network Analysis ◽  
Structural Analysis ◽  
Network Analysis ◽  
Social Research ◽  
Analysis Methods

Graphs are mathematical formalisms that represent social networks very well. Analysis methods using graph theory have started to develop substantially along with the advancement of mathematics and computer sciences in recent years, with contributions from several disciplines including social network analysis. Learning how to use graphs to represent social networks is important not only for employing theoretical insights of this advanced field in social research, but also for the practical purposes of utilizing its mature and abundant tools. This chapter explores structural analysis with graphs.

scholarly journals Social Network Analysis and Churn Prediction in Telecommunications Using Graph Theory

Entropy ◽  
2020 ◽  
Vol 22 (7) ◽  
pp. 753 ◽  
Author(s):  
Stefan M. Kostić ◽  
Mirjana I. Simić ◽  
Miroljub V. Kostić
Keyword(s):  
Graph Theory ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Churn Prediction ◽  
Network Graph ◽  
Network Analytics ◽  
Telecommunications Market ◽  
Market Saturation ◽  
Important Nodes

Due to telecommunications market saturation, it is very important for telco operators to always have fresh insights into their customer’s dynamics. In that regard, social network analytics and its application with graph theory can be very useful. In this paper we analyze a social network that is represented by a large telco network graph and perform clustering of its nodes by studying a broad set of metrics, e.g., node in/out degree, first and second order influence, eigenvector, authority and hub values. This paper demonstrates that it is possible to identify some important nodes in our social network (graph) that are vital regarding churn prediction. We show that if such a node leaves a monitored telco operator, customers that frequently interact with that specific node will be more prone to leave the monitored telco operator network as well; thus, by analyzing existing churn and previous call patterns, we proactively predict new customers that will probably churn. The churn prediction results are quantified by using top decile lift metrics. The proposed method is general enough to be readily adopted in any field where homophilic or friendship connections can be assumed as a potential churn driver.

Mining Largest Maximal Quasi-Cliques

2021 ◽  
Vol 15 (5) ◽  
pp. 1-21
Author(s):  
Seyed-Vahid Sanei-Mehri ◽  
Apurba Das ◽  
Hooman Hashemi ◽  
Srikanta Tirthapura
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Heuristic Algorithm ◽  
State Of The Art ◽  
Experimental Results ◽  
Np Hard ◽  
Challenging Problem ◽  
Current State ◽  
Clique Enumeration

Quasi-cliques are dense incomplete subgraphs of a graph that generalize the notion of cliques. Enumerating quasi-cliques from a graph is a robust way to detect densely connected structures with applications in bioinformatics and social network analysis. However, enumerating quasi-cliques in a graph is a challenging problem, even harder than the problem of enumerating cliques. We consider the enumeration of top- k degree-based quasi-cliques and make the following contributions: (1) we show that even the problem of detecting whether a given quasi-clique is maximal (i.e., not contained within another quasi-clique) is NP-hard. (2) We present a novel heuristic algorithm K ernel QC to enumerate the k largest quasi-cliques in a graph. Our method is based on identifying kernels of extremely dense subgraphs within a graph, followed by growing subgraphs around these kernels, to arrive at quasi-cliques with the required densities. (3) Experimental results show that our algorithm accurately enumerates quasi-cliques from a graph, is much faster than current state-of-the-art methods for quasi-clique enumeration (often more than three orders of magnitude faster), and can scale to larger graphs than current methods.

scholarly journals Data Mining in Social Networks and its Application in Counterterrorism

2019 ◽  
Vol 8 (3) ◽  
pp. 1278-1284
Keyword(s):  
Data Mining ◽  
Social Networks ◽  
Graph Theory ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Theory Analysis ◽  
Graph Theory Analysis ◽  
Insight Into ◽  
Novel Algorithm

Social Networks are best represented as complex interconnected graphs. Graph theory analysis can hence be used for insight into various aspects of these complex social networks. Privacy of such networks lately has been challenged and a detailed analysis of such networks is required. This paper applies key graph theory concepts to analyze such social networks. Moreover, it also discusses applications and proposal of a novel algorithm to analyze and gather key information from terrorist social networks. Investigative Data Mining is used for this which is defined as when Social Network Analysis (SNA) is applied to Terrorist Networks to gather useful insights about the network..

scholarly journals Clique Comparison and Homophily Detection in Telecom Social Networks

2019 ◽  
Vol 9 (2) ◽  
pp. 81-87
Author(s):  
Marin Mandić ◽  
Davor Škobić ◽  
Goran Martinović
Keyword(s):  
Social Networks ◽  
Graph Theory ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Phone Call ◽  
Network Data ◽  
Social Connectivity ◽  
Telecom Industry ◽  
Virtual Operator

Social Network Analysis (SNA) is based on graph theory and is used for identification of the structure, behavioral patterns and social connectivity of entities. In this paper, SNA is used in the telecom industry in terms of a call detail record referring to phone call data separated into two groups, i.e., domicile network and virtual operator network data. Emphasis was placed on community detection. Comparison was made among communities detected in domicile and virtual operator networks. Results show that in contrast to domicile network, the number of cliques in the virtual operator network is larger. Also, homophily was detected between domicile network and virtual operator network users.

scholarly journals Prospecting and modeling of primary energy production indicators in Brazil supported by graph theory

2021 ◽  
Vol 10 (10) ◽  
pp. e485101019199
Author(s):  
Mario Mollo Neto ◽  
Lucélia Maria Casagrande ◽  
Camila Pires Cremasco ◽  
Luís Roberto Almeida Gabriel Filho
Keyword(s):  
Graph Theory ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Energy Production ◽  
Primary Source ◽  
Primary Energy ◽  
Primary Sources ◽  
Energy Matrix ◽  
By Products

This research presents a study on the scenario of primary energy production in Brazil over the period from 1970 to 2018, as well as the main sources that contributed to the national energy matrix. To map trends in primary energy production, Social Network Analysis was applied. Also are presented the mathematical models that represent the variation in the centrality and density of primary energy production. Based on the results and the literature on the economy of Brazil in the period between the years 1970 to 2018, it discuss the movements carried out by public policymakers that culminated in a reduction of investments in the sector, even that demand would always be growing. However, it would continue to be linked to the results of small increases in GDP and HDI. Another result was the evolution and of oil as a non-renewable primary source offer for the entire period of the research. Was perceived the alternation of offers from non-renewable sources that, starting with the predominance of firewood, passing on to the generation of hydraulic energy, the most important for two decades, and the substitution by-products derived from sugarcane, which extends until the year 2018. It was also observed that in the period from 2010 to 2018, the share of supply from renewable primary sources, in percentage terms, it is no longer so distant from the share of offers from non-renewable primary sources, almost even dividing availability for the composition of the Brazilian matrix.

The Latest Research Progress of Personalized Information Recommend Based on the Tag

2013 ◽  
Vol 679 ◽  
pp. 131-136
Author(s):  
Hui Juan Wu ◽  
Bao Xiang Xu ◽  
Yan Yan Wang
Keyword(s):  
Graph Theory ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Research Progress ◽  
The Internet ◽  
Analysis Method ◽  
Social Tag ◽  
The Future ◽  
Information Recommendation

In web2.0 era, tag marks that users have become from passive consumers into active information creators. Users can create and use any tags which represent their will freely on the Internet; they can also share all kinds of tags which other users have created. At the same time, personalized information recommendation can solve the problem of the flood of information, so how to conduct personalized information recommendation based on tags has become the focus of many scholars. This paper summarized three categories about the information recommendation model based on tags: Graph theory- based model, Tensor-based model and Topic-based model, then the author put forward the defects of the existing model and the problems that need to be solved in the future, such as how to reduce noise, how to use social network analysis method to study social tag system and so on.

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