EXPRS: An extended pagerank method for product feature extraction from online consumer reviews

•The feature-oriented social media analytic technique is explored.•The NodeRank algorithm is proposed to rank the dependency pairs and identify product features.•The synonym lexicon is integrated to derive the complete product features.•Implicit product feature inference method in online consumer reviews is studied.

Online consumer product reviews are a main source for consumers to obtain product information and reduce product uncertainty before making a purchase decision. However, the great volume of product reviews makes it tedious and ineffective for consumers to peruse individual reviews one by one and search for comments on specific product features of their interest. This study proposes a novel method called EXPRS that integrates an extended PageRank algorithm, synonym expansion, and implicit feature inference to extract product features automatically. The empirical evaluation using consumer reviews on three different products shows that EXPRS is more effective than two baseline methods.