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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

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 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

Several behavioral, social, and public health interventions, such as suicide/HIV prevention or community preparedness against natural disasters, leverage social network information to maximize outreach. Algorithmic influence maximization…

Social and Information Networks · Computer Science 2020-12-17 Aida Rahmattalabi , Shahin Jabbari , Himabindu Lakkaraju , Phebe Vayanos , Max Izenberg , Ryan Brown , Eric Rice , Milind Tambe

The typical algorithmic problem in viral marketing aims to identify a set of influential users in a social network, who, when convinced to adopt a product, shall influence other users in the network and trigger a large cascade of adoptions.…

Machine Learning · Computer Science 2014-04-17 Nan Du , Yingyu Liang , Maria Florina Balcan , Le Song

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

A typical viral marketing model identifies influential users in a social network to maximize a single product adoption assuming unlimited user attention, campaign budgets, and time. In reality, multiple products need campaigns, users have…

Social and Information Networks · Computer Science 2017-01-31 Nan Du , Yingyu Liang , Maria-Florina Balcan , Manuel Gomez-Rodriguez , Hongyuan Zha , Le Song

Influence Maximization (IM) seeks to identify a small set of seed nodes in a social network to maximize expected information spread under a diffusion model. While community-based approaches improve scalability by exploiting modular…

Social and Information Networks · Computer Science 2026-02-03 Eliot W. Robson , Abhishek K. Umrawal

We consider the problem of allocating multiple indivisible items to a set of networked agents to maximize the social welfare subject to network externalities. Here, the social welfare is given by the sum of agents' utilities and…

Computer Science and Game Theory · Computer Science 2023-08-29 S. Rasoul Etesami

Influence maximization(IM) problem is to find a seed set in a social network which achieves the maximal influence spread. This problem plays an important role in viral marketing. Numerous models have been proposed to solve this problem.…

Social and Information Networks · Computer Science 2015-10-22 Yaxuan Wang , Hongzhi Wang , Jianzhong Li

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 graph $G$, a community structure $\mathcal{C}$, and a budget $k$, the fair influence maximization problem aims to select a seed set $S$ ($|S|\leq k$) that maximizes the influence spread while narrowing the influence gap between…

Data Structures and Algorithms · Computer Science 2023-11-23 Xiaobin Rui , Zhixiao Wang , Jiayu Zhao , Lichao Sun , Wei Chen

Influence maximization is a well-studied problem that asks for a small set of influential users from a social network, such that by targeting them as early adopters, the expected total adoption through influence cascades over the network is…

Social and Information Networks · Computer Science 2015-11-06 Wei Lu , Wei Chen , Laks V. S. Lakshmanan

Incentivized social advertising, an emerging marketing model, provides monetization opportunities not only to the owners of the social networking platforms but also to their influential users by offering a "cut" on the advertising revenue.…

Social and Information Networks · Computer Science 2021-06-23 Cigdem Aslay , Francesco Bonchi , Laks V. S. Lakshmanan , Wei Lu

Given a social network with nonuniform selection cost of the users, the problem of \textit{Budgeted Influence Maximization} (BIM in short) asks for selecting a subset of the nodes within an allocated budget for initial activation, such that…

Social and Information Networks · Computer Science 2020-04-09 Suman Banerjee , Mamata Jenamani , Dilip Kumar Pratihar

Online social networks have been one of the most effective platforms for marketing and advertising. Through "word of mouth" effects, information or product adoption could spread from some influential individuals to millions of users in…

Social and Information Networks · Computer Science 2023-05-17 Tiantian Chen , Bin Liu , Wenjing Liu , Qizhi Fang , Jing Yuan , 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

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

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

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
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