An influence framework on product word-of-mouth (WoM) measurement

With the development of e-commerce platforms, online customer reviews have become an important instrument for providing product word-of-mouth (WoM) information. Analyzing and measuring WoM is quite valuable in product design, sales prediction, marketing strategy, and other decision-making tasks. In contrast to previous studies that analyze product WoM focusing on a single product, we propose an influence framework to measure WoM from a market perspective. In this framework, we combine product competition relationships and customer intercommunication relationships to construct a two-layer network and calculate the node influence effects in the network. To compare different product WoM measures, we use product sales as a predictor and build a series of predictive models. In the experiments conducted based on Amazon.com data, we find that, first, textual sentiment analysis produces a better summary of customer opinions than rating scores. Second, product-comparative relationships provide additional information on measuring product WoM. Third, the customer intercommunication feature in social media is useful for measuring the collective opinions about a product. The influence framework and experimental findings have both theoretical and managerial implications.