# Malicious Selling Strategies in E-Commerce Livestream: A Case Study of Alibaba's Taobao and ByteDance's TikTok

arXiv: https://arxiv.org/abs/2111.10491 · HTML: https://mlsanity.com/paper/2111.10491/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Nov 2021.

## Built on by (most cited first, 1 of 1)

- [KunlunBaize: LLM with Multi-Scale Convolution and Multi-Token Prediction Under TransformerX Framework](https://mlsanity.com/paper/2503.04784/) (2025)

## Abstract (arXiv)

Due to the limitations imposed by the COVID-19 pandemic, many users have shifted their shopping patterns from offline to online. Livestream shopping has become popular as one of the online shopping media. However, many streamers' malicious selling behaviors have been reported. In this research, we sought to explore streamers' malicious selling strategies and understand how viewers perceive these strategies. First, we recorded 40 livestream shopping sessions from two popular livestream platforms in China -- Taobao and TikTok (or "Douyin" in Chinese). We identified 16 malicious selling strategies and found that platform designs enhanced these malicious selling strategies. Second, through an interview study with 13 viewers, we provide a rich description of viewers' awareness of malicious selling strategies and the challenges they encountered while trying to overcome malicious selling. We conclude by discussing the policy and design implications of countering malicious selling.