Lifestyles in Amazon: Evidence from online reviews enhanced recommender system

Yinghui Huang, Hui Liu, Weiqing Li, Zichao Wang, Xiangen Hu, and Weijun Wang

Online lifestyles have been shown to reflect and affect consumers' preferences across a wide range of online scenarios.

Introduction

The development of big marketing data and intelligent algorithms has offered exciting new opportunities for in-depth observation and understanding of user behavior, promises to be a game changer in marketing researches and applications (Sundsøy, Bjelland, Iqbal, & de Montjoye, 2014). Given the rapid growth of online shopping in the ever-growing e-commerce landscape, the understanding of online consumer behaviors can be translated into valuable insights on consumers' psychological states and traits that can, in turn, toward to real-time usercentric optimization of marketing actions (Matz & Netzer, 2017). Recommender systems are machine learning algorithms based on consumer behavior to predict their...

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