Semantics between customers and providers: The relation between product descriptions, reviews, and customer satisfaction in E-commerce
Carlos A. Rodriguez-Diaz, Sergio Jimenez, Daniel Bejarano, Julio A., Bernal-Ch\'avez, Alexander Gelbukh

TL;DR
This paper introduces a novel information-theoretical and neural embedding approach to measure the lexical-semantic gap between product descriptions and customer reviews in e-commerce, linking smaller gaps to higher customer satisfaction.
Contribution
It presents a new method combining information theory and neural embeddings to quantify semantic differences, enhancing understanding of language impact on customer satisfaction in e-commerce.
Findings
Lower lexical-semantic gaps correlate with higher customer satisfaction
Neural embeddings effectively identify words with semantic drift
The approach can be applied to improve communication in various client-relationship domains
Abstract
In social commerce, users dialogue with each other on the topics related to the providers' products. However, the language customers use may vary from the language vendors use on their e-commerce websites and product descriptions. This situation can lead to possible misunderstandings in the social dialogue between customers, and incidental costs in the dialogue between customers and vendors. One possible reason for this difference is that words used by customers may have different meanings compared to those used by product description writers. We present a novel approach to measure this potential lexical-semantic gap for various e-commerce domains using an information-theoretical approach based on a large corpus of user reviews and product descriptions. Additionally, we use neural word embeddings to identify words with the highest semantic drift between reviews and descriptions as a…
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Taxonomy
TopicsSentiment Analysis and Opinion Mining · Digital Marketing and Social Media · AI in Service Interactions
