Signed Network

2014 ◽  
pp. 1734-1734
Keyword(s):  
Signed Network

scholarly journals A signed network perspective on the government formation process in parliamentary democracies

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Angela Fontan ◽  
Claudio Altafini
Keyword(s):  
Decision Making ◽  
Formation Process ◽  
Signed Graph ◽  
Balance Theory ◽  
Collective Decision Making ◽  
Dynamical Models ◽  
Average Correlation ◽  
Parliamentary Democracies ◽  
Signed Network ◽  
The Government

AbstractIn parliamentary democracies, government negotiations talks following a general election can sometimes be a long and laborious process. In order to explain this phenomenon, in this paper we use structural balance theory to represent a multiparty parliament as a signed network, with edge signs representing alliances and rivalries among parties. We show that the notion of frustration, which quantifies the amount of “disorder” encoded in the signed graph, correlates very well with the duration of the government negotiation talks. For the 29 European countries considered in this study, the average correlation between frustration and government negotiation talks ranges between 0.42 and 0.69, depending on what information is included in the edges of the signed network. Dynamical models of collective decision-making over signed networks with varying frustration are proposed to explain this correlation.

scholarly journals Why it is important to consider negative ties when studying polarized debates: A signed network analysis of a Dutch cultural controversy on Twitter

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0256696
Author(s):  
Anna Keuchenius ◽  
Petter Törnberg ◽  
Justus Uitermark
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Network Analysis ◽  
Language Processing ◽  
User Interaction ◽  
User Interactions ◽  
Online Interactions ◽  
Network Analyses ◽  
Social Media Platforms ◽  
Signed Network

Despite the prevalence of disagreement between users on social media platforms, studies of online debates typically only look at positive online interactions, represented as networks with positive ties. In this paper, we hypothesize that the systematic neglect of conflict that these network analyses induce leads to misleading results on polarized debates. We introduce an approach to bring in negative user-to-user interaction, by analyzing online debates using signed networks with positive and negative ties. We apply this approach to the Dutch Twitter debate on ‘Black Pete’—an annual Dutch celebration with racist characteristics. Using a dataset of 430,000 tweets, we apply natural language processing and machine learning to identify: (i) users’ stance in the debate; and (ii) whether the interaction between users is positive (supportive) or negative (antagonistic). Comparing the resulting signed network with its unsigned counterpart, the retweet network, we find that traditional unsigned approaches distort debates by conflating conflict with indifference, and that the inclusion of negative ties changes and enriches our understanding of coalitions and division within the debate. Our analysis reveals that some groups are attacking each other, while others rather seem to be located in fragmented Twitter spaces. Our approach identifies new network positions of individuals that correspond to roles in the debate, such as leaders and scapegoats. These findings show that representing the polarity of user interactions as signs of ties in networks substantively changes the conclusions drawn from polarized social media activity, which has important implications for various fields studying online debates using network analysis.

scholarly journals Signed Network Embedding in Social Media

2017 ◽  
pp. 327-335 ◽  
Author(s):  
Suhang Wang ◽  
Jiliang Tang ◽  
Charu Aggarwal ◽  
Yi Chang ◽  
Huan Liu
Keyword(s):  
Social Media ◽  
Network Embedding ◽  
Signed Network

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.

The necessary and sufficient condition for clustering of nodes based on the signs of connections in generalized signed networks

2019 ◽  
Vol 33 (10) ◽  
pp. 1950086
Author(s):  
Qi Wang ◽  
Yinhe Wang ◽  
Zilin Gao ◽  
Lili Zhang ◽  
Wenli Wang
Keyword(s):  
Clustering Algorithms ◽  
Necessary Condition ◽  
Sufficient Condition ◽  
Necessary And Sufficient Condition ◽  
Signed Networks ◽  
Clustering Problem ◽  
Structural Hole ◽  
Signed Network ◽  
Necessary And Sufficient ◽  
Sufficient And Necessary Condition

This paper investigates the clustering problem for the generalized signed networks. By rigorous derivations, a sufficient and necessary condition for clustering of the nodes in generalized signed networks is proposed in this paper. In order to obtain this condition, the concept of friends group is first introduced for the nodes based on their links’ sign. Then, the unprivileged network is also defined in this paper by employing the concepts of structural hole and broker. Compared with the existing clustering algorithms, the outstanding advantage in this paper is that only the positive or negative (especially, or zero) sign of the links is required regardless of their density or sparsity. We have proved mathematically that a generalized signed network is classifiable if and only if it is an unprivileged network. Finally, two examples associated with numerical simulations are proposed to generate the unprivileged networks.

scholarly journals SignRank: A Novel Random Walking Based Ranking Algorithm in Signed Networks

2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Cong Wan ◽  
Yanhui Fang ◽  
Cong Wang ◽  
Yanxia Lv ◽  
Zejie Tian ◽  
...  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Positive Emotion ◽  
Ranking Algorithm ◽  
Random Walking ◽  
Signed Networks ◽  
Ranking Algorithms ◽  
Negative Score ◽  
Positive Score ◽  
Signed Network

Social networks have become an indispensable part of modern life. Signed networks, a class of social network with positive and negative edges, are becoming increasingly important. Many social networks have adopted the use of signed networks to model like (trust) or dislike (distrust) relationships. Consequently, how to rank nodes from positive and negative views has become an open issue of social network data mining. Traditional ranking algorithms usually separate the signed network into positive and negative graphs so as to rank positive and negative scores separately. However, much global information of signed network gets lost during the use of such methods, e.g., the influence of a friend’s enemy. In this paper, we propose a novel ranking algorithm that computes a positive score and a negative score for each node in a signed network. We introduce a random walking model for signed network which considers the walker has a negative or positive emotion. The steady state probability of the walker visiting a node with negative or positive emotion represents the positive score or negative score. In order to evaluate our algorithm, we use it to solve sign prediction problem, and the result shows that our algorithm has a higher prediction accuracy compared with some well-known ranking algorithms.

An Extend SIR Opinion Dynamic Model Base on Empirical Signed Network Mining

2014 ◽  
Vol 513-517 ◽  
pp. 2744-2747
Author(s):  
Wei Li ◽  
Pei Li ◽  
Hui Wang
Keyword(s):  
Social Network ◽  
Web Crawler ◽  
Model Base ◽  
Network Mining ◽  
Web Structure ◽  
Online Social Media ◽  
Signed Social Network ◽  
Spread Model ◽  
Signed Network ◽  
Opinion Dynamic

Relations between users on online social media sites often reflect a mixture of positive and negative interactions. The network composed by those positive and negative relations is called signed social network. We design a web crawler to collect the data base on a special web event of battle between Fang Zhouzi and Han Han. And we construct a signed social network with sentiment weighted relationships base on this empirical data. Under this empirical spread web structure, we construct an extended SIR spread model in such a signed social network with sentiment weighted relationships, and we study influence with the network factors of signed, directed and weighted on opinion spreading. Under this model, we could know the proportion of signed edges is most important factor to the spread result.

scholarly journals Attending Over Triads for Learning Signed Network Embedding

2019 ◽  
Vol 2 ◽  
Author(s):  
Shagun Sodhani ◽  
Meng Qu ◽  
Jian Tang
Keyword(s):  
Network Embedding ◽  
Signed Network
Sign in / Sign up

Export Citation Format

Share Document