Principal Investigator (PI): Asst Prof Winson Peng
Co-Principal Investigator (Co-PI): Nil
Collaborators: Dr Yingcai Wu, Dr Xiaojun Quan
Start Date: Nov 2014
End Date: On-going
Abstract: Viral marketing refers to the phenomenon by which consumers mutually share and spread marketing messages on social media, initially sent out deliberately by marketers to stimulate and capitalize on word-of-mouth behaviors. Viral marketing has emerged to be a popular practice among marketing practitioners due to the great convenience and low cost in generating and diffusing information on social media. Commercial organizations, governments, non-government organizations and the like around the world are making use of social media for products promotion, political mobilization, reputation improvement, and other purposes.
The popularity of viral marketing lies in three widely accepted assumptions: contagious diffusion of viral messages, power of influential spreaders in information diffusion, and successful identification of influential spreaders. However, these assumptions have not been systematically and empirically validated. To fill in the gap, the project proposes five Lasswellian questions about viral marketing. Particularly, the project will develop a battery of indicators to assess the temporal and topological properties of diffusion dynamics of viral messages. A new concept of “topic publics” will be introduced in the project which can refine our previous conceptualization and operationalization of influential spreaders on social media. Drawing on theories from multiple disciplines, the project will develop a multi-level model to examine the impacts of messages characteristics, topic publics, and structural positions of marketers and seeds on diffusion dynamics of viral messages.
To address proposed research questions, we will analyze time-stamped viral messages and other structural information retrieved from Twitter over the past three years. The findings of the project can advance our understanding of information diffusion mechanism on social media, which can be generalized to other contexts, such as health information, political information, and rumors. It can also help marketing practitioners optimize the practical performance of viral marketing campaigns and quantitatively assess the performance of viral marketing campaigns.