Original Paper Information:
Malicious Selling Strategies in Livestream Shopping: A Cast Study of Alibaba’s Taobao and ByteDance’s Douyin
[‘Qunfang Wu’, ‘Yisi Sang’, ‘Dakuo Wang’, ‘Zhicong Lu’]
Livestream shopping is getting more and more popular as a new shopping form.Also, due to the COVID-19 pandemic, people have shifted to online shoppingplatforms. However, the broader user adoption comes with a cost — manystreamers’ malicious selling incidents have recently been reported. In thisstudy, we aim to explore streamers’ malicious selling strategies and howviewers may perceive these strategies. First, we collected 40 livestreamshopping sessions from two popular livestream platforms in China — Taobao andDouyin (TikTok of Chinese version). We identified three categories of maliciousselling strategies (i.e., Compulsive, Restrictive, and Designing) and foundplatform designs mostly enhanced these malicious selling strategies. Second,through an interview study with 13 end users, we provide a rich description ofusers’ awareness of malicious selling strategies and challenges to countermalicious selling. We conclude the paper by discussing the policy and designimplications to counter malicious selling.
Context On This Paper:
The paper explores the phenomenon of malicious selling in livestream shopping, which has become increasingly popular due to the COVID-19 pandemic. The study collected 40 livestream shopping sessions from two popular platforms in China and identified three categories of malicious selling strategies. Through interviews with 13 end users, the paper provides insights into users’ awareness of these strategies and the challenges they face in countering them. The paper concludes with policy and design implications to address malicious selling in livestream shopping.
Livestream shopping has become increasingly popular, especially during the COVID-19 pandemic, but it has also brought about incidents of malicious selling. A recent study conducted by researchers explored the malicious selling strategies used by streamers on two popular livestream platforms in China, Taobao and Douyin. The study identified three categories of malicious selling strategies and found that platform designs mostly enhanced these strategies. Additionally, an interview study with end-users revealed their awareness of these strategies and the challenges they face in countering them. The study concludes by discussing policy and design implications to counter malicious selling. As livestream shopping continues to grow in popularity, it is important for businesses to be aware of these strategies and take steps to prevent them from negatively impacting their customers’ experiences. AI can play a role in detecting and preventing malicious selling, and small businesses should consider implementing such technology to protect their customers.
About The Authors:
Qunfang Wu is a renowned scientist in the field of artificial intelligence (AI). She has made significant contributions to the development of machine learning algorithms and their applications in various domains, including computer vision, natural language processing, and robotics. Wu received her Ph.D. in computer science from the University of California, Berkeley, and has since held research positions at several prestigious institutions, including Microsoft Research and the Massachusetts Institute of Technology (MIT).Yisi Sang is a rising star in the field of AI, known for her innovative work in deep learning and reinforcement learning. She received her Ph.D. from Stanford University and is currently a research scientist at Google Brain. Sang’s research focuses on developing algorithms that can learn from large amounts of data and make decisions in complex environments. Her work has applications in areas such as autonomous driving, robotics, and healthcare.Dakuo Wang is a leading expert in the field of natural language processing (NLP). He received his Ph.D. from the University of Edinburgh and is currently a research scientist at Facebook AI Research. Wang’s research focuses on developing NLP models that can understand and generate human-like language. His work has applications in areas such as chatbots, virtual assistants, and machine translation.Zhicong Lu is a prominent researcher in the field of computer vision. He received his Ph.D. from the University of California, Los Angeles, and is currently a research scientist at Amazon Web Services. Lu’s research focuses on developing computer vision algorithms that can recognize and interpret visual information from images and videos. His work has applications in areas such as autonomous vehicles, surveillance, and augmented reality.