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We consider the fractional influence maximization problem, i.e., identifying users on a social network to be incentivized with potentially partial discounts to maximize the influence on the network. The larger the discount given to a user,…

Social and Information Networks · Computer Science 2024-07-09 Akhil Bhimaraju , Eliot W. Robson , Lav R. Varshney , Abhishek K. Umrawal

CMO Council reports that 71\% of internet users in the U.S. were influenced by coupons and discounts when making their purchase decisions. It has also been shown that offering coupons to a small fraction of users (called seed users) may…

Social and Information Networks · Computer Science 2018-02-23 Shaojie Tang

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

Most previous work on influence maximization in social networks is limited to the non-adaptive setting in which the marketer is supposed to select all of the seed users, to give free samples or discounts to, up front. A disadvantage of this…

Social and Information Networks · Computer Science 2016-04-28 Sharan Vaswani , Laks V. S. Lakshmanan

For the purpose of propagating information and ideas through a social network, a seeding strategy aims to find a small set of seed users that are able to maximize the spread of the influence, which is termed as influence maximization…

Social and Information Networks · Computer Science 2016-07-05 Guangmo Tong , Weili Wu , Shaojie Tang , Ding-Zhu Du

Now-a-days, Online Social Networks (OSNs) are extensively used by different commercial houses for viral marketing. The key problem that arises in this context is to choose a limited number of highly influential users as the initial adopters…

Social and Information Networks · Computer Science 2026-01-23 Poonam Sharma , Suman Banerjee

Now-a-days, \emph{Online Social Networks} have been predominantly used by commercial houses for viral marketing where the goal is to maximize profit. In this paper, we study the problem of Profit Maximization in the two\mbox{-}phase…

Databases · Computer Science 2022-07-19 Poonam Sharma , Suman Banerjee

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

We consider the problem of devising incentive strategies for viral marketing of a product. In particular, we assume that the seller can influence penetration of the product by offering two incentive programs: a) direct incentives to…

Social and Information Networks · Computer Science 2012-03-02 Pankaj Dayama , Aditya Karnik , Y. Narahari

The idea of social advertising (or social promotion) is to select a group of influential individuals (a.k.a \emph{seeds}) to help promote some products or ideas through an online social networks. There are two major players in the social…

Data Structures and Algorithms · Computer Science 2021-10-01 Shaojie Tang , Jing Yuan

We study the use of viral marketing strategies on social networks to maximize revenue from the sale of a single product. We propose a model in which the decision of a buyer to buy the product is influenced by friends that own the product…

Data Structures and Algorithms · Computer Science 2009-02-23 David Arthur , Rajeev Motwani , Aneesh Sharma , Ying Xu

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

One key problem in network analysis is the so-called influence maximization problem, which consists in finding a set $S$ of at most $k$ seed users, in a social network, maximizing the spread of information from $S$. This paper studies a…

Computer Science and Game Theory · Computer Science 2020-03-19 Ruben Becker , Gianlorenzo D'Angelo , Hugo Gilbert

In this paper, we study a strategic model of marketing and product consumption in social networks. We consider two competing firms in a market providing two substitutable products with preset qualities. Agents choose their consumptions…

Social and Information Networks · Computer Science 2014-04-08 Arastoo Fazeli , Amir Ajorlou , Ali Jadbabaie

In a social network, even about the same information the excitements between different pairs of users are different. If you want to spread a piece of new information and maximize the expected total amount of excitements, which seed users…

Social and Information Networks · Computer Science 2016-10-26 Zhefeng Wang , Yu Yang , Jian Pei , Enhong Chen

Diffusion of information, innovation, and ideas is an important phenomenon in social networks. Information propagates through the network and reaches from one person to the next. In many settings, it is meaningful to restrict diffusion so…

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

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 investigate the novel problem of voting-based opinion maximization in a social network: Find a given number of seed nodes for a target campaigner, in the presence of other competing campaigns, so as to maximize a voting-based score for…

Social and Information Networks · Computer Science 2022-09-15 Arkaprava Saha , Xiangyu Ke , Arijit Khan , Laks V. S. Lakshmanan

In this paper, we study the problem of allocating ads to users through the viral-marketing lens. Advertisers approach the host with a budget in return for the marketing campaign service provided by the host. We show that allocation that…

Social and Information Networks · Computer Science 2015-08-26 Cigdem Aslay , Wei Lu , Francesco Bonchi , Amit Goyal , Laks V. S. Lakshmanan

We identify influential early adopters in a social network, where individuals are resource constrained, to maximize the spread of multiple, costly behaviors. A solution to this problem is especially important for viral marketing. The…

Social and Information Networks · Computer Science 2017-02-08 Kaushik Sarkar , Hari Sundaram
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