Online social networks are increasingly being recognized as an important source of information influencing the adoption and use of products and services. Viral marketing—the tactic of creating a process where interested people can market to each other—is therefore emerging as an important means to spread-the-word and stimulate the trial, adoption, and use of products and services. Consider the case of Hotmail, one of the earliest firms to tap the potential of viral marketing. Based predominantly on publicity from word-of-mouse [4], the Web-based email service provider garnered one million registered subscribers in its first six months, hit two million subscribers two months later, and passed the eleven million mark in eighteen months [7]. Wired magazine put this growth in perspective in its December 1998 issue: “The Hotmail user base grew faster than [that of ] any media company in history—faster than CNN, faster than AOL, even faster than Seinfeld’s audience. By mid-2000, Hotmail had over 66 million users with 270,000 new accounts being established each day.” While the potential of viral marketing to efficiently reach out to a broad set of potential users is attracting considerable attention, the value of this approach is also being questioned [5]. There needs to be a greater understanding of the contexts in which this strategy works and the characteristics of products and services for which it is most effective. This is particularly important because the inappropriate use of viral marketing can be counterproductive by creating unfavorable attitudes towards products. Work examining this phenomenon currently provides either descriptive accounts of particular initiatives [8] or advice based on anecdotal evidence [2]. What is missing is an analysis of viral marketing that highlights systematic patterns in the nature of knowledge-sharing and persuasion by influencers and responses by recipients in online social networks. To this end, we propose an organizing framework for viral marketing that draws on prior theory and highlights different behavioral mechanisms underlying knowledge-sharing, influence, and compliance in online social networks. Though the framework is descrip-
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