Discovering influential nodes for viral marketing

Yung-Ming Li*, Cheng Yang Lai, Chia Hao Lin

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

Abstract

High cost and uncertainty are problems of marketing. Influential online product reviews are more powerful than firm's advertisements. The key of viral marketing is to discover the viruses for efficiently spreading product impressions. In this paper, a model combined with mining techniques and adaptive RFM is proposed to evaluate the influential power of online reviewers. The modified PMI equation quantifies the review value and the RFM concept is used to consider the writing status of reviewers for the influence calculation. The artificial neural network is also adopted to train the appropriate network structure in our model. Trust, the most common influential power indicator, is then used to evaluate our model. The results showed that our model outperforms two general methods in selecting influential reviewers. Our work can accurately point out which reviewer to be selected to become the virus.

Original languageEnglish
Title of host publicationProceedings of the 42nd Annual Hawaii International Conference on System Sciences, HICSS
DOIs
StatePublished - 3 Apr 2009
Event42nd Annual Hawaii International Conference on System Sciences, HICSS - Waikoloa, HI, United States
Duration: 5 Jan 20099 Jan 2009

Publication series

NameProceedings of the 42nd Annual Hawaii International Conference on System Sciences, HICSS

Conference

Conference42nd Annual Hawaii International Conference on System Sciences, HICSS
CountryUnited States
CityWaikoloa, HI
Period5/01/099/01/09

Fingerprint Dive into the research topics of 'Discovering influential nodes for viral marketing'. Together they form a unique fingerprint.

  • Cite this

    Li, Y-M., Lai, C. Y., & Lin, C. H. (2009). Discovering influential nodes for viral marketing. In Proceedings of the 42nd Annual Hawaii International Conference on System Sciences, HICSS [4755612] (Proceedings of the 42nd Annual Hawaii International Conference on System Sciences, HICSS). https://doi.org/10.1109/HICSS.2009.163