Direct marketing has evolved rapidly with new data sources, including web analytics and social media measurement. One of the keys to direct marketing is the ability to measure its effects, and in this aspect, social media brings some challenges. However, more and more work is being done to understand how information spreads through social networks and how this propagation can be quantified/modeled mathematically.
Such is the case with recent research at the Rochester Institute of Technology where the Psychology Department and Math Department are teaming up to understand how rumors (both positive and negative) are spread. The mathematical model developed suggests propagation is based on the motivations that individuals have for spreading the rumor, their belief in the rumor, and the “novelty” of the rumor.
This research has implications for marketers, as companies grapple with their images and the popularity of their products among the social network chatter. Although message propagation is more likely within a close-knit network of “like-minded” individuals, a company will benefit more when its message can cross over to a slightly broader audience (finding new “evangelists” to take up their cause).
However, in reference to social media specifically, there is a question whether some of the Twitter and Facebook networks that exist are stable enough for the message propagation represented in the research. And perhaps the most important question is whether any company’s marketing message is “novel” enough to get the support it needs to propagate even within the tightest networks.
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