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Related papers: Multi-Round Influence Maximization

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As a widely observable social effect, influence diffusion refers to a process where innovations, trends, awareness, etc. spread across the network via the social impact among individuals. Motivated by such social effect, the concept of…

Social and Information Networks · Computer Science 2020-12-24 Liang Ma

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 study the influence minimization problem: given a graph $G$ and a seed set $S$, blocking at most $b$ nodes or $b$ edges such that the influence spread of the seed set is minimized. This is a pivotal yet underexplored aspect of network…

Databases · Computer Science 2024-12-06 Jiadong Xie , Fan Zhang , Kai Wang , Jialu Liu , Xuemin Lin , Wenjie Zhang

Viral marketing campaigns target primarily those individuals who are central in social networks and hence have social influence. Marketing events, however, may attract diverse audience. Despite the importance of event marketing, the…

Social and Information Networks · Computer Science 2022-01-04 Balázs R. Sziklai , Balázs Lengyel

Influence maximization has been studied for social network analysis, such as viral marketing (advertising), rumor prevention, and opinion leader identification. However, most studies neglect the interplay between influence spread, cost…

Social and Information Networks · Computer Science 2025-09-10 Mingyang Feng , Qi Zhao , Shan He , Yuhui Shi

Influence Maximization (IM) is to identify the seed set to maximize information dissemination in a network. Elegant IM algorithms could naturally extend to cases where each node is equipped with a specific weight, reflecting individual…

Social and Information Networks · Computer Science 2024-12-11 Xinyan Su , Zhiheng Zhang , Jiyan Qiu

We consider the problem of maximizing the spread of influence in a social network by choosing a fixed number of initial seeds, formally referred to as the influence maximization problem. It admits a $(1-1/e)$-factor approximation algorithm…

Social and Information Networks · Computer Science 2022-06-15 Grant Schoenebeck , Biaoshuai Tao

This paper examines the problem of adaptive influence maximization in social networks. As adaptive decision making is a time-critical task, a realistic feedback model has been considered, called myopic. In this direction, we propose the…

Social and Information Networks · Computer Science 2018-07-09 Guillaume Salha , Nikolaos Tziortziotis , Michalis Vazirgiannis

We consider the revenue maximization problem in social advertising, where a social network platform owner needs to select seed users for a group of advertisers, each with a payment budget, such that the total expected revenue that the owner…

Data Structures and Algorithms · Computer Science 2021-07-27 Kai Han , Benwei Wu , Jing Tang , Shuang Cui , Cigdem Aslay , Laks V. S. Lakshmanan

Influence maximization serves as the main goal of a variety of social network activities such as viral marketing and campaign advertising. The independent cascade model for the influence spread assumes a one-time chance for each activated…

Social and Information Networks · Computer Science 2017-08-08 Ali Vardasbi , Heshaam Faili , Masoud Asadpour

The billboard advertisement has emerged as an effective out-of-home advertisement technique where the objective is to choose a limited number of slots to play some advertisement content (e.g., animation, video, etc.) with the hope that the…

Databases · Computer Science 2025-10-24 Dildar Ali , Suman Banerjee , Yamuna Prasad

We address the problem of influence maximization when the social network is accompanied by diffusion cascades. In prior works, such information is used to compute influence probabilities, which is utilized by stochastic diffusion models in…

Social and Information Networks · Computer Science 2020-11-23 George Panagopoulos , Fragkiskos D. Malliaros , Michalis Vazirgiannis

Finding the seed set that maximizes the influence spread over a network is a well-known NP-hard problem. Though a greedy algorithm can provide near-optimal solutions, the subproblem of influence estimation renders the solutions inefficient.…

Machine Learning · Computer Science 2023-10-17 George Panagopoulos , Nikolaos Tziortziotis , Michalis Vazirgiannis , Fragkiskos D. Malliaros

In the study of social networks, a fundamental problem is that of influence maximization (IM): How can we maximize the collective opinion of individuals in a network given constrained marketing resources? Traditionally, the IM problem has…

Disordered Systems and Neural Networks · Physics 2016-09-30 Christopher Lynn , Daniel D. Lee

The identification of the minimal set of nodes that maximizes the propagation of information is one of the most relevant problems in network science. In this paper, we introduce a new method to find the set of initial spreaders to maximize…

The idea of social advertising (or social promotion) is to select a group of influential individuals (a.k.a \emph{seeds}) to help promote some products or ideas through an online social networks. There are two major players in the social…

Data Structures and Algorithms · Computer Science 2021-10-01 Shaojie Tang , Jing Yuan

In this paper, we study the Budgeted Influence Maximization with Delay Problem, for which the number of literature are limited. We propose an approximate marginal spread computation\mbox{-}based approach for solving this problem. The…

Social and Information Networks · Computer Science 2020-05-26 Suman Banerjee , Mamata Jenamani , Dilip Kumar Pratihar

Profit Maximization is one of the key objectives for social media marketing, where the task is to choose a limited number of highly influential nodes such that their initial activation leads to maximum profit. In this paper, we introduce a…

Social and Information Networks · Computer Science 2025-12-23 Poonam Sharma , Suman Banerjee

One key problem in network analysis is the so-called influence maximization problem, which consists in finding a set $S$ of at most $k$ seed users, in a social network, maximizing the spread of information from $S$. This paper studies a…

Computer Science and Game Theory · Computer Science 2020-03-19 Ruben Becker , Gianlorenzo D'Angelo , Hugo Gilbert

Social Media Advertisement has emerged as an effective approach for promoting the brands of a commercial house. Hence, many of them have started using this medium to maximize the influence among the users and create a customer base. In…

Social and Information Networks · Computer Science 2025-04-02 Poonam Sharma , Dildar Ali , Suman Banerjee