The Volume and Valence of Electronic Word-of-mouth in Social Websites: A Simulation Modeling Approach Using Network Topologies and Artificial Neural Networks

With the growing popularity of online social websites, it is becoming increasingly important for marketing researchers to understand, measure and forecast the electronic word-of mouth (EWOM) activities of consumers. The two most important WOM attributes studied in the extant literature are volume and valence. This paper provides computational models to predict the development of volume and valence of EWOM in social websites. With the data from large-scale web-crawling activities, meta-analysis and a series of computer simulations, the authors developed mathematical models for predicting EWOM volume and valence. The EWOM volume models used theories of network
topologies and the EWOM valence model used an artificial neural network model. Moreover, Twitter was utilized as a particularly relevant example of social websites to demonstrate the applications of the aforementioned models in EWOM marketing. The authors discussed the insights from the findings and
suggest EWOM marketing strategies to optimize the performance of EWOM volume and valence in social websites. Finally, the authors propose several suggestions for future research with regard to EWOM marketing based on the authors’ findings.