Marketing in Random Networks
| dc.creator | Amini, Hamed | |
| dc.creator | Draief, Moez | |
| dc.creator | Lelarge, Marc | |
| dc.date | 2008-05-21 | |
| dc.date | 2008-09-07 | |
| dc.date.accessioned | 2026-07-07T10:00:54Z | |
| dc.date.available | 2026-07-07T10:00:54Z | |
| dc.description | 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 promotion of new products or the diffusion of technologies. A social network can be represented by a graph where the nodes are individuals and the edges indicate a form of social relationship. The flow of influence through this network can be thought of as an increasing process of active nodes: as individuals become aware of new technologies, they have the potential to pass them on to their neighbours. The goal of marketing is to trigger a large cascade of adoptions. In this paper, we develop a mathematical model that allows to analyze the dynamics of the cascading sequence of nodes switching to the new technology. To this end we describe a continuous-time and a discrete-time models and analyse the proportion of nodes that adopt the new technology over time. | |
| dc.description | to appear NetCoop 2008 | |
| dc.identifier | https://arxiv.org/abs/0805.3155 | |
| dc.identifier | http://arxiv.org/abs/0805.3155 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/168464 | |
| dc.subject | Computer Science and Game Theory | |
| dc.title | Marketing in Random Networks | |
| dc.type | text |