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Related papers: Interest Maximization in Social Networks

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Online social networks have become an important platform for people to communicate, share knowledge and disseminate information. Given the widespread usage of social media, individuals' ideas, preferences and behavior are often influenced…

Social and Information Networks · Computer Science 2023-09-12 Hui Li , Susu Yang , Mengting Xu , Sourav S Bhowmick , Jiangtao Cui

Influence Maximization (IM) is a classical combinatorial optimization problem, which can be widely used in mobile networks, social computing, and recommendation systems. It aims at selecting a small number of users such that maximizing the…

Social and Information Networks · Computer Science 2023-06-16 Yandi Li , Haobo Gao , Yunxuan Gao , Jianxiong Guo , Weili Wu

A social network (SN) is a social structure consisting of a group representing the interaction between them. SNs have recently been widely used and, subsequently, have become suitable and popular platforms for product promotion and…

Social and Information Networks · Computer Science 2022-09-13 Saeid Ghafouri , Seyed Hossein Khasteh , Seyed Omid Azarkasb

The information flows among the people while they communicate through social media websites. Due to the dependency on digital media, a person shares important information or regular updates with friends and family. The set of persons on…

Social and Information Networks · Computer Science 2024-06-14 Rahul Kumar Gautam , Anjeneya Swami Kare , Durga Bhavani S

Social networks are commonly used for marketing purposes. For example, free samples of a product can be given to a few influential social network users (or "seed nodes"), with the hope that they will convince their friends to buy it. One…

Social and Information Networks · Computer Science 2019-01-17 Siyu Lei , Silviu Maniu , Luyi Mo , Reynold Cheng , Pierre Senellart

Influence maximization (IM) aims to identify a small number of influential individuals to maximize the information spread and finds applications in various fields. It was first introduced in the context of viral marketing, where a company…

Social and Information Networks · Computer Science 2023-06-06 Shiqi Zhang , Yiqian Huang , Jiachen Sun , Wenqing Lin , Xiaokui Xiao , Bo Tang

Influence maximization (IM) has garnered a lot of attention in the literature owing to applications such as viral marketing and infection containment. It aims to select a small number of seed users to adopt an item such that adoption…

Social and Information Networks · Computer Science 2020-12-08 Prithu Banerjee , Wei Chen , Laks V. S. Lakshmanan

In many real-world scenarios, an individual's local social network carries significant influence over the opinions they form and subsequently propagate. In this paper, we propose a novel diffusion model -- the Pressure Threshold model (PT)…

Social and Information Networks · Computer Science 2026-04-03 Curt Stutsman , Eliot W. Robson , Abhishek K. Umrawal

Influence maximization (IM) is a classic problem that aims to identify a small group of critical individuals, known as seeds, who can influence the largest number of users in a social network through word-of-mouth. This problem finds…

Social and Information Networks · Computer Science 2024-10-23 Yiqian Huang , Shiqi Zhang , Laks V. S. Lakshmanan , Wenqing Lin , Xiaokui Xiao , Bo Tang

Influence Maximization (IM) is the task of determining k optimal influential nodes in a social network to maximize the influence spread using a propagation model. IM is a prominent problem for viral marketing, and helps significantly in…

Social and Information Networks · Computer Science 2022-11-18 Inder Khatri , Arjun Choudhry , Aryaman Rao , Aryan Tyagi , Dinesh Kumar Vishwakarma , Mukesh Prasad

Influence maximization (IM) aims at maximizing the spread of influence by offering discounts to influential users (called seeding). In many applications, due to user's privacy concern, overwhelming network scale etc., it is hard to target…

Social and Information Networks · Computer Science 2020-10-06 Chen Feng , Luoyi Fu , Bo Jiang , Haisong Zhang , Xinbing Wang , Feilong Tang , Guihai Chen

The influence maximization (IM) problem aims at finding a subset of seed nodes in a social network that maximize the spread of influence. In this study, we focus on a sub-class of IM problems, where whether the nodes are willing to be the…

Social and Information Networks · Computer Science 2021-06-15 Haipeng Chen , Wei Qiu , Han-Ching Ou , Bo An , Milind Tambe

Influence Maximization (IM) aims to maximize the number of people that become aware of a product by finding the `best' set of `seed' users to initiate the product advertisement. Unlike prior arts on static social networks containing fixed…

Social and Information Networks · Computer Science 2019-11-14 Xudong Wu , Luoyi Fu , Zixin Zhang , Jingfan Meng , Xinbing Wang , Guihai Chen

Given a social network $G$ and an integer $k$, the influence maximization (IM) problem asks for a seed set $S$ of $k$ nodes from $G$ to maximize the expected number of nodes influenced via a propagation model. The majority of the existing…

Social and Information Networks · Computer Science 2020-04-15 Keke Huang , Jing Tang , Kai Han , Xiaokui Xiao , Wei Chen , Aixin Sun , Xueyan Tang , Andrew Lim

Influence Maximization(IM) aims to identify highly influential nodes to maximize influence spread in a network. Previous research on the IM problem has mainly concentrated on single-layer networks, disregarding the comprehension of the…

Physics and Society · Physics 2023-11-16 Su-Su Zhang , Ming Xie , Chuang Liu , Xiu-Xiu Zhan

In this paper, we present an algorithmic study on how to surpass competitors in popularity by strategic promotions in social networks. We first propose a novel model, in which we integrate the Preferential Attachment (PA) model for…

Social and Information Networks · Computer Science 2024-09-18 Hao Liao , Sheng Bi , Jiao Wu , Wei Zhang , Mingyang Zhou , Rui Mao , Wei Chen

Given a social network with diffusion probabilities as edge weights and an integer k, which k nodes should be chosen for initial injection of information to maximize influence in the network? This problem is known as Target Set Selection in…

Social and Information Networks · Computer Science 2018-08-17 Suman Banerjee , Mamata Jenamani , Dilip Kumar Pratihar

We consider influence maximization (IM) in social networks, which is the problem of maximizing the number of users that become aware of a product by selecting a set of "seed" users to expose the product to. While prior work assumes a known…

Machine Learning · Computer Science 2018-05-25 Sharan Vaswani , Branislav Kveton , Zheng Wen , Mohammad Ghavamzadeh , Laks Lakshmanan , Mark Schmidt

The Influence Maximization (IM) problem is a well-known NP-hard combinatorial problem over graphs whose goal is to find the set of nodes in a network that spreads influence at most. Among the various methods for solving the IM problem,…

Social and Information Networks · Computer Science 2024-05-17 Stefano Genetti , Eros Ribaga , Elia Cunegatti , Quintino Francesco Lotito , Giovanni Iacca

Influence Maximization (IM), which aims to select a set of users from a social network to maximize the expected number of influenced users, has recently received significant attention for mass communication and commercial marketing.…

Social and Information Networks · Computer Science 2022-05-12 Taotao Cai , Qi Lei , Quan Z. Sheng , Shuiqiao Yang , Jian Yang , Wei Emma Zhang
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