The Effects of the Social Structure of Digital Networks on Viral Marketing Performance

By Mauro Bampo, Michael T. Ewing, Dineli R. Mather, David Stewart, Mark Wallace. Information systems research, 2008

402 citations recorded by the source corpus.

Viral marketing is a form of peer-to-peer communication in which individuals are encouraged to pass on promotional messages within their social networks. Conventional wisdom holds that the viral marketing process is both random and unmanageable. In this paper, we deconstruct the process and investigate the formation of the activated digital network as distinct from the underlying social network. We then consider the impact of the social structure of digital networks (random, scale free, and small world) and of the transmission behavior of individuals on campaign performance. Specifically, we identify alternative social network models to understand the mediating effects of the social structures of these models on viral marketing campaigns. Next, we analyse an actual viral marketing campaign and use the empirical data to develop and validate a computer simulation model for viral marketing. Finally, we conduct a number of simulation experiments to predict the spread of a viral message within different types of social network structures under different assumptions and scenarios. Our findings confirm that the social structure of digital networks play a critical role in the spread of a viral message. Managers seeking to optimize campaign performance should give consideration to these findings before designing and implementing viral marketing campaigns. We also demonstrate how a simulation model is used to quantify the impact of campaign management inputs and how these learnings can support managerial decision making.

Subfields: Sociology and Political Science, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/cd22e3547af06f6ae5e65ca7a9814c1a277087c6

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Sociology and Political Science

In Statistical and Nonlinear Physics

Citations in the corpus

Advertisements on Facebook: Identifying the persuasive elements in the development of positive attitudes in consumers (2018, background): “Several scholarly articles on promotional marketing (Bampo et al. 2008; Hinz et al. 2014; Van der Lans et al. 2010; Schulze et al., 2014) analyzing the effect of advertisement and how consumers evaluate advertisements, clearly identified that the impact of advertisements on consumers’ minds potentia”
What's Different about Social Media Networks? A Framework and Research Agenda (2014, background): “Studies of how content spreads and influences users in a social media network have been of considerable interest (Aral and Walker 2011; Bampo et al. 2008; Hinz et al. 2011), especially considering the early adoption of social media tools for marketing purposes (Fader and Winer 2012).”
Validity Issues in the Use of Social Network Analysis with Digital Trace Data (2011, neutral): “Agarwal et al. (2008) put it thus: "Most transactions and conversations in these online groups leave a digital trace…this research data makes visible social processes that are much more difficult to study in conventional organizational settings."”
Seeding Strategies for Viral Marketing: An Empirical Comparison (2011, background): “network (Bampo et al. 2008); (3) the behavioral characteristics of the recipients and their incentives for sharing the message (Arndt 1967); and (4) the seeding strategy, which determines the initial set of targeted consumers chosen by the initiator of the viral marketing campaign (Bampo et al. 2008”
The Emotions that Drive Viral Video (2013, background): “How to effectively manage a campaign by optimising targeting and seeding efforts (Bampo et al., 2008; Hinz et al., 2011); 3.”