Assessing product competitive advantages from the perspective of customers by mining user-generated content on social media

摘要

User-generated content (UGC) is becoming increasingly available on social media for a wide range of products and services. Such UGC contains rich information about customer attitudes, opinions, and experiences. We propose a novel method for product competitive advantage analysis, which provides an essential basis for quality management and marketing strategy development, by mining UGC. Compared to traditional product performance analysis methods based on manufacturers' internal data and expert reviews, our method better reflects the perspective of customers. While a few recent methods based on UGC analysis assess the performance of one product in isolation, our method reveals the competitive advantages (and disadvantages) of a target product relative to its competitors. Our method uses supervised learning to identify competitors from UGC and domain-specific sentiment analysis to quantify customer attitudes. A case study in the automotive industry demonstrates the utility of the method.