scholarly journals Computing global structural balance in large-scale signed social networks

2011 ◽  
Vol 108 (52) ◽  
pp. 20953-20958 ◽  
Author(s):  
G. Facchetti ◽  
G. Iacono ◽  
C. Altafini
Keyword(s):  
Social Networks ◽  
Large Scale ◽  
Structural Balance ◽  
Signed Social Networks

Partition signed social networks by spectral features and structural balance

2019 ◽  
Vol 33 (19) ◽  
pp. 1950211
Author(s):  
Xiaoyu Zhu ◽  
Yinghong Ma
Keyword(s):  
Social Networks ◽  
Social Systems ◽  
Structural Balance ◽  
The Social ◽  
Signed Social Networks ◽  
Spectral Algorithm ◽  
Community People ◽  
Signed Network ◽  
The Stability ◽  
The Relationship

In social networks, individuals are usually but not exactly divided into communities such that within each community people are friendly to each other while being hostile towards other communities. This is in line with structural balance theory which enables a comprehensive understanding of the stability and tensions of social systems. Yet, there may be some conflicts such as the intra-community negative edges or inter-community positive edges that affect the balancedness of the social system. This raises an interesting question of how to partition a signed network for minimal conflicts, i.e., maximum balancedness. In this paper, by analyzing the relationship between balancedness and spectrum space, we find that each eigenvector can be an indicator of dichotomous structure of networks. Incorporating the leader mechanism, we partition signed networks to maximize the balancedness with top-k eigenvectors. Moreover, we design an optimizing segment to further improve the balancedness of the network. Experimental data both from real social and synthetic networks demonstrate that the spectral algorithm has higher efficiency, robustness and scientificity.

Analysis of opinion spreading in signed social networks under the impact of structural balance

2015 ◽  
Vol 29 (13) ◽  
pp. 1550079 ◽  
Author(s):  
Pei Li ◽  
Yini Zhang ◽  
Su He ◽  
Hui Wang
Keyword(s):  
Social Networks ◽  
Common Phenomenon ◽  
Structural Balance ◽  
User Influence ◽  
Signed Social Networks ◽  
Different Types ◽  
Negative Links ◽  
The Impact ◽  
Negative Relationships

Social networks have attracted remarkable attention and it is of great importance to understand the process of opinion spreading in popular social networks. However, most research on diffusion cannot be applied directly to investigate social networks, where relationships are heterogeneous and structural balance is a common phenomenon. In this paper, we propose models to characterize the process of opinion spreading in signed social networks under the impact of structural balance. We classify users into different types according to the numbers of their positive links, and define the term user influence to represent the average number of times that users are influenced, which is incurred by a user spreading an opinion. We then propose an approach to analyze the user influence theoretically and the analysis accuracy is verified by simulations. We observe that the user influence increases with user type and also increases with the fraction of negative links in the network if this fraction value exceeds some point. That's to say, negative relationships may enhance opinion spreading if we consider the impact of structural balance, which is an interesting result.

scholarly journals A Community-Based Approach for Link Prediction in Signed Social Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Saeed Reza Shahriary ◽  
Mohsen Shahriari ◽  
Rafidah MD Noor
Keyword(s):  
Social Networks ◽  
Community Detection ◽  
Link Prediction ◽  
Large Scale ◽  
Prediction Problem ◽  
Signed Graphs ◽  
Community Based ◽  
Ranking Algorithms ◽  
Detection Approach ◽  
Signed Social Networks

In signed social networks, relationships among nodes are of the types positive (friendship) and negative (hostility). One absorbing issue in signed social networks is predicting sign of edges among people who are members of these networks. Other than edge sign prediction, one can define importance of people or nodes in networks via ranking algorithms. There exist few ranking algorithms for signed graphs; also few studies have shown role of ranking in link prediction problem. Hence, we were motivated to investigate ranking algorithms availed for signed graphs and their effect on sign prediction problem. This paper makes the contribution of using community detection approach for ranking algorithms in signed graphs. Therefore, community detection which is another active area of research in social networks is also investigated in this paper. Community detection algorithms try to find groups of nodes in which they share common properties like similarity. We were able to devise three community-based ranking algorithms which are suitable for signed graphs, and also we evaluated these ranking algorithms via sign prediction problem. These ranking algorithms were tested on three large-scale datasets: Epinions, Slashdot, and Wikipedia. We indicated that, in some cases, these ranking algorithms outperform previous works because their prediction accuracies are better.

scholarly journals Minimum Memory-Based Sign Adjustment in Signed Social Networks

Entropy ◽  
2019 ◽  
Vol 21 (8) ◽  
pp. 728
Author(s):  
Mingze Qi ◽  
Hongzhong Deng ◽  
Yong Li
Keyword(s):  
Social Networks ◽  
Small World ◽  
Network Size ◽  
Initial Ratio ◽  
Structural Balance ◽  
Local Sign ◽  
Signed Social Network ◽  
Signed Social Networks ◽  
Symmetric Relations ◽  
And Control

In social networks comprised of positive (P) and negative (N) symmetric relations, individuals (nodes) will, under the stress of structural balance, alter their relations (links or edges) with their neighbours, either from positive to negative or vice versa. In the real world, individuals can only observe the influence of their adjustments upon the local balance of the network and take this into account when adjusting their relationships. Sometime, their local adjustments may only respond to their immediate neighbourhoods, or centre upon the most important neighbour. To study whether limited memory affects the convergence of signed social networks, we introduce a signed social network model, propose random and minimum memory-based sign adjustment rules, and analyze and compare the impacts of an initial ratio of positive links, rewire probability, network size, neighbor number, and randomness upon structural balance under these rules. The results show that, with an increase of the rewiring probability of the generated network and neighbour number, it is more likely for the networks to globally balance under the minimum memory-based adjustment. While the Newmann-Watts small world model (NW) network becomes dense, the counter-intuitive phenomena emerges that the network will be driven to a global balance, even under the minimum memory-based local sign adjustment, no matter the network size and initial ratio of positive links. This can help to manage and control huge networks with imited resources.

scholarly journals World War III Analysis Using Signed Social Networks

2021 ◽  
Author(s):  
Ranjana Roy Chowdhury ◽  
Shivam Gupta ◽  
Sravanthi Chede
Keyword(s):  
Social Networks ◽  
Signed Graph ◽  
Balance Theory ◽  
World War ◽  
Recent Period ◽  
Data Set ◽  
Structural Balance ◽  
Signed Social Networks ◽  
Signed Network ◽  
World War Iii

Abstract In the recent period of time with a lot of social platforms emerging, the relationships among various units can be framed with respect to either positive, negative or no relation. These units can be individuals, countries or others that form the basic structural component of a signed network. These signed networks picture a dynamic characteristic of the graph so formed allowing only few combinations of signs that brings the structural balance theorem in picture. Structural balance theory affirms that signed social networks tend to be organized so as to avoid conflictual situations, corresponding to cycles of unstable relations. The aim of structural balance in networks is to find proper partitions of nodes that guarantee equilibrium in the system allowing only few combination triangles with signed edges to be permitted in graph. Most of the works in this field of networking have either explained the importance of signed graph or have applied the balance theorem and tried to solve problems. Following the recent time trends with each nation emerging to be superior and competing to be the best, the probable doubt of happening of WW-III(World War-III) comes into every individuals mind. Nevertheless, our paper aims at answering some of the interesting questions on World War-III. In this project we have worked with the creation of a signed graph picturing the World War-III participating countries as nodes and have predicted the best possible coalition of countries that will be formed during war. Also, we have visually depicted the number of communities that will be formed in this war and the participating countries in each communities. Our paper involves extensive analysis on the various parameters influencing the above predictions and also creation of a new data-set of World War -III that contains the pairwise relationship data of countries with various parameters influencing prediction. This paper also validates and analyses the predicted result.

Sign in / Sign up

Export Citation Format

Share Document