# A BERT based Ensemble Approach for Sentiment Classification of Customer Reviews and its Application to Nudge Marketing in e-Commerce

arXiv: https://arxiv.org/abs/2311.10782 · HTML: https://mlsanity.com/paper/2311.10782/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 6 of its 21 references that are in the map.
- First posted on arXiv 16 Nov 2023.

## Builds on (most cited first, 6 of 6)

- [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://mlsanity.com/paper/1907.11692/) (2019)
- [XLNet: Generalized Autoregressive Pretraining for Language Understanding](https://mlsanity.com/paper/1906.08237/) (2019)
- [Ups and Downs: Modeling the Visual Evolution of Fashion Trends with One-Class Collaborative Filtering](https://mlsanity.com/paper/1602.01585/) (2016)
- [Learning Natural Language Inference with LSTM](https://mlsanity.com/paper/1512.08849/) (2015)
- [Comparison Lift: Bandit-based Experimentation System for Online Advertising](https://mlsanity.com/paper/2009.07899/) (2020)
- [A Batched Multi-Armed Bandit Approach to News Headline Testing](https://mlsanity.com/paper/1908.06256/) (2019)

## Abstract (arXiv)

According to the literature, Product reviews are an important source of information for customers to support their buying decision. Product reviews improve customer trust and loyalty. Reviews help customers in understanding what other customers think about a particular product and helps in driving purchase decisions. Therefore, for an e-commerce platform it is important to understand the sentiments in customer reviews to understand their products and services, and it also allows them to potentially create positive consumer interaction as well as long lasting relationships. Reviews also provide innovative ways to market the products for an ecommerce company. One such approach is Nudge Marketing. Nudge marketing is a subtle way for an ecommerce company to help their customers make better decisions without hesitation.