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Related papers: Interest Maximization in Social Networks

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Influence maximization is the problem of finding influential users, or nodes, in a graph so as to maximize the spread of information. It has many applications in advertising and marketing on social networks. In this paper, we study a highly…

Social and Information Networks · Computer Science 2017-10-25 Paul Lagrée , Olivier Cappé , Bogdan Cautis , Silviu Maniu

The problem of influence maximization is to select the most influential individuals in a social network. With the popularity of social network sites, and the development of viral marketing, the importance of the problem has been increased.…

Social and Information Networks · Computer Science 2019-04-30 Maryam Adineh , Mostafa Nouri-Baygi

Influence maximization (IM) is the problem of finding for a given $s\geq 1$ a set $S$ of $|S|=s$ nodes in a network with maximum influence. With stochastic diffusion models, the influence of a set $S$ of seed nodes is defined as the…

Machine Learning · Computer Science 2019-10-30 Gal Sadeh , Edith Cohen , Haim Kaplan

Influence maximization (IM) is an important topic in network science where a small seed set is chosen to maximize the spread of influence on a network. Recently, this problem has attracted attention on temporal networks where the network…

Social and Information Networks · Computer Science 2023-07-04 Eric Yanchenko , Tsuyoshi Murata , Petter Holme

Influence maximization is the problem of selecting top $k$ seed nodes in a social network to maximize their influence coverage under certain influence diffusion models. In this paper, we propose a novel algorithm IRIE that integrates a new…

Social and Information Networks · Computer Science 2012-03-20 Kyomin Jung , Wooram Heo , Wei Chen

Influence Maximization Problem (IMP) is selecting a seed set of nodes in the social network to spread the influence as widely as possible. It has many applications in multiple domains, e.g., viral marketing is frequently used for new…

Databases · Computer Science 2020-01-23 Xinxun Zeng , Shiqi Zhang , Bo Tang

Influence Maximization (IM) is a pivotal concept in social network analysis, involving the identification of influential nodes within a network to maximize the number of influenced nodes, and has a wide variety of applications that range…

Social and Information Networks · Computer Science 2025-09-10 Matteo Bergamaschi , Sara Venturini , Francesco Tudisco , Francesco Rinaldi

Influence Maximization (IM), which aims to select a set of users from a social network to maximize the expected number of influenced users, is an evergreen hot research topic. Its research outcomes significantly impact real-world…

Social and Information Networks · Computer Science 2025-03-28 Taotao Cai , Quan Z. Sheng , Xiangyu Song , Jian Yang , Shuang Wang , Wei Emma Zhang , Jia Wu , Philip S. Yu

Influence maximization is the task of selecting a small number of seed nodes in a social network to maximize the influence spread from these seeds. It has been widely investigated in the past two decades. In the canonical setting, the…

Social and Information Networks · Computer Science 2022-02-21 Zhijie Zhang , Wei Chen , Xiaoming Sun , Jialin Zhang

Influence maximization is the task of finding k seed nodes in a social network such that the expected number of activated nodes in the network (under certain influence propagation model), referred to as the influence spread, is maximized.…

Social and Information Networks · Computer Science 2019-10-21 Wei Chen , Ruihan Wu , Zheng Yu

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

Since its introduction in 2003, the influence maximization (IM) problem has drawn significant research attention in the literature. The aim of IM is to select a set of k users who can influence the most individuals in the social network.…

Social and Information Networks · Computer Science 2019-06-19 Hui Li , Mengting Xu , Sourav S Bhowmick , Changsheng Sun , Zhongyuan Jiang , Jiangtao Cui

The rise of Online Social Networks (OSNs) has caused an insurmountable amount of interest from advertisers and researchers seeking to monopolize on its features. Researchers aim to develop strategies for determining how information is…

Machine Learning · Statistics 2018-03-09 Trisha Lawrence

Influence maximization is the problem of finding a set of influential users in a social network such that the expected spread of influence under a certain propagation model is maximized. Much of the previous work has neglected the important…

Social and Information Networks · Computer Science 2016-11-18 Wei Lu , Laks V. S. Lakshmanan

In the context of influence propagation in a social graph, we can identify three orthogonal dimensions - the number of seed nodes activated at the beginning (known as budget), the expected number of activated nodes at the end of the…

Discrete Mathematics · Computer Science 2011-11-08 Amit Goyal , Francesco Bonchi , Laks V. S. Lakshmanan , Suresh Venkatasubramanian

Influence maximization (IM) aims to find seed users on an online social network to maximize the spread of information about a target product through word-of-mouth propagation among all users. Prior IM methods mostly focus on maximizing the…

Social and Information Networks · Computer Science 2024-02-27 Ying Wang , Yanhao Wang

The problem of Profit Maximization asks to choose a limited number of influential users from a given social network such that the initial activation of these users maximizes the profit earned at the end of the diffusion process. This…

Social and Information Networks · Computer Science 2026-02-03 Poonam Sharma , Suman Banerjee

In recent years, social networking platforms have gained significant popularity among the masses like connecting with people and propagating ones thoughts and opinions. This has opened the door to user-specific advertisements and…

Social and Information Networks · Computer Science 2022-11-18 Aaryan Gupta , Inder Khatri , Arjun Choudhry , Pranav Chandhok , Dinesh Kumar Vishwakarma , Mukesh Prasad

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 well-known Influence Maximization (IM) problem has been actively studied by researchers over the past decade, with emphasis on marketing and social networks. Existing research have obtained solutions to the IM problem by obtaining the…

Machine Learning · Statistics 2018-11-06 Trisha Lawrence