On modeling product advertisement in social networks

  • Authors:
  • Bridge Zhao;y. K. Li;John C.S. Lui;Dah-Ming Chiu

  • Affiliations:
  • The Chinese University of Hong Kong;The Chinese University of Hong Kong;The Chinese University of Hong Kong;The Chinese University of Hong Kong

  • Venue:
  • ACM SIGMETRICS Performance Evaluation Review
  • Year:
  • 2009

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Abstract

Advertising via social networks is receiving more attention these days. Given a fixed investment (e.g., free samples), a company needs to find out the final probability that users will purchase the product. In this paper we characterize and model various influence mechanisms that govern the word-of-mouth spread of advertisements in large social networks. We use the local mean field (LMF) technique to analyze large scale networks wherein states of nodes can be changed by various influence mechanisms. Extensive simulations are carried out to validate the accuracy of our model, and the results also provide insights on designing advertising strategies.