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In this paper, we propose a new data based model for influence maximization in online social networks. We use the theory of belief functions to overcome the data imperfection problem. Besides, the proposed model searches to detect…

社会与信息网络 · 计算机科学 2016-10-21 Siwar Jendoubi , Arnaud Martin , Ludovic Liétard , Hend Hadji , Boutheina Yaghlane

The influence maximization is the problem of finding a set of social network users, called influencers, that can trigger a large cascade of propagation. Influencers are very beneficial to make a marketing campaign goes viral through social…

社会与信息网络 · 计算机科学 2017-08-29 Siwar Jendoubi , Arnaud Martin

Information diffusion and influence maximization are important and extensively studied problems in social networks. Various models and algorithms have been proposed in the literature in the context of the influence maximization problem. A…

计算机科学与博弈论 · 计算机科学 2015-03-18 Mayur Mohite , Y. Narahari

Influence maximization is the problem of selecting a set of influential users in the social network. Those users could adopt the product and trigger a large cascade of adoptions through the " word of mouth " effect. In this paper, we…

社会与信息网络 · 计算机科学 2017-01-23 Siwar Jendoubi , Arnaud Martin , Ludovic Liétard , Ben Hend , Ben Boutheina

Online social networks provide a medium for citizens to form opinions on different societal issues, and a forum for public discussion. They also expose users to viral content, such as breaking news articles. In this paper, we study the…

社会与信息网络 · 计算机科学 2022-04-11 Sijing Tu , Stefan Neumann

In traditional models for word-of-mouth recommendations and viral marketing, the objective function has generally been based on reaching as many people as possible. However, a number of studies have shown that the indiscriminate spread of a…

社会与信息网络 · 计算机科学 2017-11-10 Rediet Abebe , Lada Adamic , Jon Kleinberg

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…

社会与信息网络 · 计算机科学 2012-03-02 Pankaj Dayama , Aditya Karnik , Y. Narahari

Viral marketing is different from other marketing strategies since it leverages the influence power in intimate relationship, e.g., close friends, family members, couples. Due to the development and popularity of social networking services,…

数据结构与算法 · 计算机科学 2015-06-29 Hong-Han Shuai

Viral marketing takes advantage of preexisting social networks among customers to achieve large changes in behaviour. Models of influence spread have been studied in a number of domains, including the effect of "word of mouth" in the…

计算机科学与博弈论 · 计算机科学 2008-09-08 Hamed Amini , Moez Draief , Marc Lelarge

Influencer marketing involves a wide range of strategies in which brands collaborate with popular content creators (i.e., influencers) to leverage their reach, trust, and impact on their audience to promote and endorse products or services.…

计算与语言 · 计算机科学 2023-09-07 Danae Sánchez Villegas , Catalina Goanta , Nikolaos Aletras

We introduce and discuss kinetic models of opinion formation on social networks in which the distribution function depends on both the opinion and the connectivity of the agents. The opinion formation model is subsequently coupled with a…

物理与社会 · 物理学 2018-08-22 G. Toscani , A. Tosin , M. Zanella

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…

数据结构与算法 · 计算机科学 2009-02-23 David Arthur , Rajeev Motwani , Aneesh Sharma , Ying Xu

We present an analysis of a person-to-person recommendation network, consisting of 4 million people who made 16 million recommendations on half a million products. We observe the propagation of recommendations and the cascade sizes, which…

物理与社会 · 物理学 2007-05-23 Jure Leskovec , Lada A. Adamic , Bernardo A. Huberman

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…

社会与信息网络 · 计算机科学 2017-10-25 Paul Lagrée , Olivier Cappé , Bogdan Cautis , Silviu Maniu

The process of opinion formation through synthesis and contrast of different viewpoints has been the subject of many studies in economics and social sciences. Today, this process manifests itself also in online social networks and social…

社会与信息网络 · 计算机科学 2013-02-01 Aristides Gionis , Evimaria Terzi , Panayiotis Tsaparas

From its origins in the mid 90s, the application of the concept of virality to commercial communication has represented an opportunity for brands to cross the traditional barriers of the audience concerning advertising and turn it into…

社会与信息网络 · 计算机科学 2015-05-11 Alberto Dafonte-Gomez

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…

社会与信息网络 · 计算机科学 2024-02-27 Ying Wang , Yanhao Wang

Viral campaigns are crucial methods for word-of-mouth marketing in social communities. The goal of these campaigns is to encourage people for activity. The problem of incentivised and non-incentivised campaigns is studied in the paper.…

社会与信息网络 · 计算机科学 2013-03-12 Radosław Michalski , Jarosław Jankowski , Przemysław Kazienko

This thesis can be categorized under the Influencer Marketing industry with respect to social media initiatives. Influencer marketing is a modern tactic used by brands to enhance their visibility to their target audience by using the…

计算机与社会 · 计算机科学 2017-10-25 Neha Joshi

The goal of opinion maximization is to maximize the positive view towards a product, an ideology or any entity among the individuals in social networks. So far, opinion maximization is mainly studied as finding a set of influential nodes…

社会与信息网络 · 计算机科学 2019-01-03 Anuj Nayak , Seyyedali Hosseinalipour , Huaiyu Dai
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