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Related papers: VAIM: Visual Analytics for Influence Maximization

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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

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 the problem of identifying a limited number of initial influential users within a social network to maximize the number of influenced users. However, previous research has mostly focused on individual…

Social and Information Networks · Computer Science 2024-03-29 Zirui Yuan , Minglai Shao , Zhiqian Chen

Influence maximization (IM), which selects a set of $k$ users (called seeds) to maximize the influence spread over a social network, is a fundamental problem in a wide range of applications such as viral marketing and network monitoring.…

Social and Information Networks · Computer Science 2019-01-30 Yanhao Wang , Qi Fan , Yuchen Li , Kian-Lee Tan

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 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

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

Influence maximization (IM) is formulated as selecting a set of initial users from a social network to maximize the expected number of influenced users. Researchers have made great progress in designing various traditional methods, and…

Social and Information Networks · Computer Science 2023-05-09 Chen Ling , Junji Jiang , Junxiang Wang , My Thai , Lukas Xue , James Song , Meikang Qiu , Liang Zhao

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 (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 is the task of finding a set of seed nodes in a social network such that the influence spread of these seed nodes based on certain influence diffusion model is maximized. Topic-aware influence diffusion models have…

Social and Information Networks · Computer Science 2014-11-24 Wei Chen , Tian Lin , Cheng Yang

Social networks represent nowadays in many contexts the main source of information transmission and the way opinions and actions are influenced. For instance, generic advertisements are way less powerful than suggestions from our contacts.…

Neural and Evolutionary Computing · Computer Science 2021-05-03 Kateryna Konotopska , Giovanni Iacca

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

Given its vast application on online social networks, Influence Maximization (IM) has garnered considerable attention over the last couple of decades. Due to the intricacy of IM, most current research concentrates on estimating the…

Social and Information Networks · Computer Science 2023-04-14 Zonghan Zhang , Zhiqian Chen

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

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

Viral marketing on social networks, also known as Influence Maximization (IM), aims to select k users for the promotion of a target item by maximizing the total spread of their influence. However, most previous works on IM do not explore…

Social and Information Networks · Computer Science 2021-10-04 Ya-Wen Teng , Yishuo Shi , Chih-Hua Tai , De-Nian Yang , Wang-Chien Lee , Ming-Syan Chen

Social connections are conduits through which individuals communicate, information propagates, and diseases spread. Identifying individuals who are more likely to adopt ideas and spread them is essential in order to develop effective…

Social and Information Networks · Computer Science 2024-10-31 Vedran Sekara , Ivan Dotu , Manuel Cebrian , Esteban Moro , Manuel Garcia-Herranz

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

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
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