Rationales Derived from Seeking the Stars: A Global XAI Approach for Star Rating Estimations of Reasoning LLMs Based on Textual Online Consumer Reviews

Online consumer reviews are a key element of ecommerce platforms. To process online consumer reviews, large language models (LLMs) are very popular. For instance, they can be used to detect reviews with inconsistencies between the sentiment in the review text and star rating. This is important as such reviews harm consumer trust on the platform. However, the internal workings of LLMs are nontransparent, thus there is a strong demand for explainable AI (XAI) approaches in e-commerce. Recently, reasoning LLMs have been proposed which offer exciting opportunities here. In this study, we present a global XAI decision tree for star rating estimations of reasoning LLMs based on the review texts by deriving features from their thinking process. Our proposed approach yields higher fidelity compared to alternatives and provides comprehensible insights on star rating estimations of reasoning LLMs. In that way, this study supports ecommerce platforms to develop more trustworthy purchasing experiences.