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Related papers: Targeting influence in a harmonic opinion model

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We study distributed non-convex optimization on a time-varying multi-agent network. Each node has access to its own smooth local cost function, and the collective goal is to minimize the sum of these functions. We generalize the results…

Optimization and Control · Mathematics 2016-12-06 Tatiana Tatarenko , Behrouz Touri

Fads, product adoption, mobs, rumors, memes, and emergent norms are diverse social contagions that have been modeled as network cascades. Empirical study of these cascades is vulnerable to what we describe as the "opacity problem": the…

Social and Information Networks · Computer Science 2018-11-21 George Berry , Christopher J. Cameron , Patrick Park , Michael W. Macy

Constrained submodular set function maximization problems often appear in multi-agent decision-making problems with a discrete feasible set. A prominent example is the problem of multi-agent mobile sensor placement over a discrete domain.…

Optimization and Control · Mathematics 2021-08-02 Navid Rezazadeh , Solmaz S. Kia

The harmonic influence is a measure of the importance of nodes in social networks, which can be approximately computed by a distributed message-passing algorithm. In this extended abstract we look at two open questions about this algorithm.…

Optimization and Control · Mathematics 2018-04-20 Wilbert Samuel Rossi , Paolo Frasca

We initiate a systematic study on $\mathit{dynamic}$ $\mathit{influence}$ $\mathit{maximization}$ (DIM). In the DIM problem, one maintains a seed set $S$ of at most $k$ nodes in a dynamically involving social network, with the goal of…

Data Structures and Algorithms · Computer Science 2021-12-30 Binghui Peng

We consider random instances of non-convex perceptron problems in the high-dimensional limit of a large number of examples $M$ and weights $N$, with finite load $\alpha = M/N$. We develop a formalism based on replica theory to predict the…

Disordered Systems and Neural Networks · Physics 2026-02-11 Elizaveta Demyanenko , Davide Straziota , Carlo Baldassi , Carlo Lucibello

We present a novel software suite for social network modeling and opinion diffusion processes. Much research on social network science has assumed networks with static topologies. More recently, attention has been turned to networks that…

Social and Information Networks · Computer Science 2020-06-25 Patrick Shepherd , Mia Weaver , Judy Goldsmith

In this paper, we propose a new data based model for influence maximization in online social networks. We use the theory of belief functions to overcome the data imperfection problem. Besides, the proposed model searches to detect…

Social and Information Networks · Computer Science 2016-10-21 Siwar Jendoubi , Arnaud Martin , Ludovic Liétard , Hend Hadji , Boutheina Yaghlane

Motivated by applications such as viral marketing, the problem of influence maximization (IM) has been extensively studied in the literature. The goal is to select a small number of users to adopt an item such that it results in a large…

Social and Information Networks · Computer Science 2019-06-03 Prithu Banerjee , Wei Chen , Laks V. S. Lakshmanan

In this paper, we study a model of opinion dynamics in a social network in the presence increasing interpersonal influence, i.e., increasing peer pressure. Each agent in the social network has a distinct social stress function given by a…

Social and Information Networks · Computer Science 2017-06-20 Justin Semonsen , Christopher Griffin , Anna Squicciarini , Sarah Rajtmajer

Influence maximization is the problem of finding a subset of the most influential individuals in a network. The impact of social networks on the dissemination of information and the development of viral marketing has made this problem as…

Social and Information Networks · Computer Science 2020-12-08 Maryam Adineh , Mostafa Nouri-Baygi

We consider the canonical problem of influence maximization in social networks. Since the seminal work of Kempe, Kleinberg, and Tardos, there have been two largely disjoint efforts on this problem. The first studies the problem associated…

Social and Information Networks · Computer Science 2018-01-24 Eric Balkanski , Nicole Immorlica , Yaron Singer

We study a stochastic model for the diffusion of competing opinions in a population composed of three types of agents: trend-followers, opposers, and indifferent individuals. The decision dynamics are driven by reinforcement mechanisms,…

Probability · Mathematics 2025-06-24 Manuel González-Navarrete

We consider a brand with a given budget that wants to promote a product over multiple rounds of influencer marketing. In each round, it commissions an influencer to promote the product over a social network, and then observes the subsequent…

Machine Learning · Computer Science 2019-11-11 Shatian Wang , Zhen Xu , Van-Anh Truong

Problem definition: Corporate brands, grassroots activists, and ordinary citizens all routinely employ Word-of-mouth (WoM) diffusion to promote products and instigate social change. Our work models the formation and spread of negative…

Social and Information Networks · Computer Science 2021-05-07 Shuoguang Yang , Shatian Wang , Van-Anh Truong

Network autocorrelation models are widely used to evaluate the impact of social influence on some variable of interest. This is a large class of models that parsimoniously accounts for how one's neighbors influence one's own behaviors or…

Social and Information Networks · Computer Science 2020-05-21 Daniel K. Sewell

Part I of this paper formulated a multitask optimization problem where agents in the network have individual objectives to meet, or individual parameter vectors to estimate, subject to a smoothness condition over the graph. A diffusion…

Multiagent Systems · Computer Science 2019-11-18 Roula Nassif , Stefan Vlaski , Cedric Richard , Ali H. Sayed

We introduce and study a novel majority-based opinion diffusion model. Consider a graph $G$, which represents a social network. Assume that initially a subset of nodes, called seed nodes or early adopters, are colored either black or white,…

Data Structures and Algorithms · Computer Science 2020-12-08 Ahad N. Zehmakan

In Part I of this paper, we proposed and analyzed a novel algorithmic framework for the minimization of a nonconvex (smooth) objective function, subject to nonconvex constraints, based on inner convex approximations. This Part II is devoted…

Information Theory · Computer Science 2017-04-05 Gesualdo Scutari , Francisco Facchinei , Lorenzo Lampariello , Peiran Song , Stefania Sardellitti

In this work, we focus on strategies to influence the opinion dynamics of a well-connected society. We propose a generalization of the popular voter model. This variant of the voter model can capture a wide range of individuals including…

Social and Information Networks · Computer Science 2020-02-17 Arunabh Saxena , Bhumesh Kumar , Anmol Gupta , Neeraja Sahasrabudhe , Sharayu Moharir
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