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In social commerce, users dialogue with each other on the topics related tothe providers' products. However, the language customers use may vary from thelanguage vendors use on their e-commerce websites and product descriptions.This situation can lead to possible misunderstandings in the social dialoguebetween customers, and incidental costs in the dialogue between customers andvendors. One possible reason for this difference is that words used bycustomers may have different meanings compared to those used by productdescription writers. We present a novel approach to measure this potentiallexical-semantic gap for various e-commerce domains using aninformation-theoretical approach based on a large corpus of user reviews andproduct descriptions. Additionally, we use neural word embeddings to identifywords with the highest semantic drift between reviews and descriptions as atool to construct a ground truth for the task. We found that low levels oflexical-semantic gap are related to better customer satisfaction. Besides, thiswork is a step towards a better understanding of the effect of the use oflanguage in e-commerce and social commerce. Potential applications of thistechnology could lead to better communication between customers andimprovements in customer satisfaction, services, and revenue. Furthermore, thisstudy opens up perspectives for applications in other domains withrelationships beyond client-vendor, such as citizen-government andpatient-healthcare system.

Semantics between customers and providers: The relation between product descriptions, reviews, and customer satisfaction in E-commerce