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The social networks that infectious diseases spread along are typically clustered. Because of the close relation between percolation and epidemic spread, the behavior of percolation in such networks gives insight into infectious disease…

Quantitative Methods · Quantitative Biology 2009-05-14 Joel C Miller

In social networks, control of rumor spread is an active area of research. SIR model is generally used to study the rumor dynamics in network while considering the rumor as an epidemic. In disease spreading model, epidemic is controlled by…

Social and Information Networks · Computer Science 2015-09-29 Anoop Mehta , Ruchir Gupta

The Identification of the influential nodes in networks is one of the most promising domains. In this paper, we present an improved iterative resource allocation (IIRA) method by considering the centrality information of neighbors and the…

Physics and Society · Physics 2015-09-30 Lin-Feng Zhong , Jian-Guo Liu , Ming-Sheng Shang

The ubiquity of social platforms has reshaped the way information, behaviors, and advertisements diffuse across networks, with influence propagation often initiated by a small set of ``seed'' users. While much of the literature emphasizes…

Social and Information Networks · Computer Science 2026-05-28 Fangzhu Shen , Amir Gilad , Sudeepa Roy

Information flow, opinion, and epidemics spread over structured networks. When using individual node centrality indicators to predict which nodes will be among the top influencers or spreaders in a large network, no single centrality has…

Social and Information Networks · Computer Science 2020-11-30 Doina Bucur

In today's world, individuals interact with each other in more complicated patterns than ever. Some individuals engage through online social networks (e.g., Facebook, Twitter), while some communicate only through conventional ways (e.g.,…

Physics and Society · Physics 2015-09-15 Yong Zhuang , Osman Yağan

Spreading is a ubiquitous process in the social, biological and technological systems. Therefore, identifying influential spreaders, which is important to prevent epidemic spreading and to establish effective vaccination strategies, is full…

Physics and Society · Physics 2017-10-17 Senbin Yu , Liang Gao , Yi-Fan Wang , Ge Gao , Congcong Zhou , Zi-You Gao

Influence maximization is a widely used model for information dissemination in social networks. Recent work has employed such interventions across a wide range of social problems, spanning public health, substance abuse, and international…

Computer Science and Game Theory · Computer Science 2019-03-27 Alan Tsang , Bryan Wilder , Eric Rice , Milind Tambe , Yair Zick

Social networks have increasingly become important and popular in modern times. Moreover, the influence of social networks plays a vital role in various organizations including government organizations, academic research or corporate…

Social and Information Networks · Computer Science 2022-03-01 WC Yeh , CL Huang , TY Hsu , Z Liu , SY Tan

The advent of online social networks has facilitated fast and wide spread of information. However, some users, especially members of minority groups, may be less likely to receive information spreading on the network, due to their…

Social and Information Networks · Computer Science 2025-12-18 Changan Liu , Xiaotian Zhou , Ahad N. Zehmakan , Zhongzhi Zhang

We consider the problem of identifying rumor sources in a network, in which rumor spreading obeys a time-slotted susceptible-infected model. Unlike existing approaches, our proposed algorithm identifies as sources those nodes, which when…

Signal Processing · Electrical Eng. & Systems 2018-10-02 Jiachun Pan , Wenyi Zhang

In this paper, we address the important issue of uncertainty in the edge influence probability estimates for the well studied influence maximization problem --- the task of finding $k$ seed nodes in a social network to maximize the…

Social and Information Networks · Computer Science 2016-06-14 Wei Chen , Tian Lin , Zihan Tan , Mingfei Zhao , Xuren Zhou

We study the spread of influence in a social network based on the Linear Threshold model. We derive an analytical expression for evaluating the expected size of the eventual influenced set for a given initial set, using the probability of…

Other Computer Science · Computer Science 2010-02-09 Srinivasan Venkatramanan , Anurag Kumar

We consider the problem of selecting a seed set to maximize the expected number of influenced nodes in the social network, referred to as the \textit{influence maximization} (IM) problem. We assume that the topology of the social network is…

Machine Learning · Computer Science 2019-11-26 Xiaojin Zhang

The problem of selecting an optimal seed set to maximise influence in networks has been a subject of intense research in recent years. However, despite numerous works addressing this area, it remains a topic that requires further…

Social and Information Networks · Computer Science 2025-04-16 Michał Czuba , Piotr Bródka

We study the problem of robust influence maximization in dynamic diffusion networks. In line with recent works, we consider the scenario where the network can undergo insertion and removal of nodes and edges, in discrete time steps, and the…

Databases · Computer Science 2024-12-17 Arkaprava Saha , Bogdan Cautis , Xiaokui Xiao , Laks V. S. Lakshmanan

In a "tipping" model, each node in a social network, representing an individual, adopts a property or behavior if a certain number of his incoming neighbors currently exhibit the same. In viral marketing, a key problem is to select an…

Social and Information Networks · Computer Science 2013-09-13 Paulo Shakarian , Sean Eyre , Damon Paulo

Modern social media platforms play an important role in facilitating rapid dissemination of information through their massive user networks. Fake news, misinformation, and unverifiable facts on social media platforms propagate disharmony…

Machine Learning · Computer Science 2023-10-24 Mor Oren-Loberman , Vered Azar , Wasim Huleihel

In the adaptive influence maximization problem, we are given a social network and a budget $k$, and we iteratively select $k$ nodes, called seeds, in order to maximize the expected number of nodes that are reached by an influence cascade…

Social and Information Networks · Computer Science 2021-05-06 Gianlorenzo D'Angelo , Debashmita Poddar , Cosimo Vinci

The Shapley value has been recently advocated as a method to choose the seed nodes for the process of information diffusion. Intuitively, since the Shapley value evaluates the average marginal contribution of a player to the coalitional…

Artificial Intelligence · Computer Science 2014-09-30 Kamil Adamczewski , Szymon Matejczyk , Tomasz P. Michalak
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