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A topic propagating in a social network reaches its tipping point if the number of users discussing it in the network exceeds a critical threshold such that a wide cascade on the topic is likely to occur. In this paper, we consider the task…

Social and Information Networks · Computer Science 2014-06-19 Peng Zhang , Wei Chen , Xiaoming Sun , Yajun Wang , Jialin Zhang

In this paper, we study the Multi-Round Influence Maximization (MRIM) problem, where influence propagates in multiple rounds independently from possibly different seed sets, and the goal is to select seeds for each round to maximize the…

Social and Information Networks · Computer Science 2019-06-07 Lichao Sun , Weiran Huang , Philip S. Yu , Wei 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

We consider the problem of maximizing the spread of influence in a social network by choosing a fixed number of initial seeds --- a central problem in the study of network cascades. The majority of existing work on this problem, formally…

Social and Information Networks · Computer Science 2016-09-22 Rico Angell , Grant Schoenebeck

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

The influence maximization paradigm has been used by researchers in various fields in order to study how information spreads in social networks. While previously the attention was mostly on efficiency, more recently fairness issues have…

Social and Information Networks · Computer Science 2021-11-10 Ruben Becker , Gianlorenzo D'Angelo , Sajjad Ghobadi , Hugo Gilbert

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

Given a budget and arbitrary cost for selecting each node, the budgeted influence maximization (BIM) problem concerns selecting a set of seed nodes to disseminate some information that maximizes the total number of nodes influenced (termed…

Social and Information Networks · Computer Science 2013-01-23 Huy Nguyen , Rong Zheng

We consider the problem of Influence Maximization (IM), the task of selecting $k$ seed nodes in a social network such that the expected number of nodes influenced is maximized. We propose a community-aware divide-and-conquer framework that…

Social and Information Networks · Computer Science 2023-02-21 Abhishek K. Umrawal , Christopher J. Quinn , Vaneet Aggarwal

The influence maximization (IM) problem as defined in the seminal paper by Kempe et al. has received widespread attention from various research communities, leading to the design of a wide variety of solutions. Unfortunately, this classical…

Databases · Computer Science 2017-09-28 Hui Li , Sourav S Bhowmick , Jiangtao Cui , Jianfeng Ma

The rapid development of social networks has a wide range of social effects, which facilitates the study of social issues. Accurately forecasting the information propagation process within social networks is crucial for promptly…

Social and Information Networks · Computer Science 2024-03-12 Xinyu Li , Yutong Guo , Jixuan He , Jiacheng Zhao , Chenwei Wang

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

The majority of influence maximization (IM) studies focus on targeting influential seeders to trigger substantial information spread in social networks. In this paper, we consider a new and complementary problem of how to further increase…

Social and Information Networks · Computer Science 2017-06-27 Yishi Lin , Wei Chen , John C. S. Lui

Influence maximization, the fundamental of viral marketing, aims to find top-$K$ seed nodes maximizing influence spread under certain spreading models. In this paper, we study influence maximization from a game perspective. We propose a…

Artificial Intelligence · Computer Science 2020-06-04 Yu Zhang , Yan Zhang

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

Traditional viral marketing problems aim at selecting a subset of seed users for one single product to maximize its awareness in social networks. However, in real scenarios, multiple products can be promoted in social networks at the same…

Social and Information Networks · Computer Science 2016-07-05 Jiawei Zhang , Senzhang Wang , Qianyi Zhan , Philip S. Yu

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

In this paper, we study the problem of robust influence maximization in the independent cascade model under a hyperparametric assumption. In social networks users influence and are influenced by individuals with similar characteristics and…

Machine Learning · Computer Science 2019-05-14 Dimitris Kalimeris , Gal Kaplun , Yaron Singer

We introduce a new threshold model of social networks, in which the nodes influenced by their neighbours can adopt one out of several alternatives. We characterize the graphs for which adoption of a product by the whole network is possible…

Social and Information Networks · Computer Science 2015-03-19 Krzysztof R. Apt , Evangelos Markakis

Recently the influence maximization problem has received much attention for its applications on viral marketing and product promotions. However, such influence maximization problems have not taken into account the monetary effect on the…

Social and Information Networks · Computer Science 2015-05-26 Ya-Wen Teng , Chih-Hua Tai , Philip S. Yu , Ming-Syan Chen