Paper Info
Title
Understanding Social Influence in Collective Product Ratings Using Behavioral and Cognitive Metrics
Abstract
ABSTRACT Online platforms commonly collect and display user-generated information to support subsequent users’ decision-making. However, studies have noticed that presenting collective information can pose social influences on individuals’ opinions and alter their preferences accordingly. It is essential to deepen understanding of people’s preferences when exposed to others’ opinions and the underlying cognitive mechanisms to address potential biases. Hence, we conducted a laboratory study to investigate how products’ ratings and reviews influence participants’ stated preferences and cognitive responses assessed by their Electroencephalography (EEG) signals. The results showed that social ratings and reviews could alter participants’ preferences and affect their status of attention, working memory, and emotion. We further conducted predictive analyses to show that participants’ Electroencephalography-based measures can achieve higher power than behavioral measures to discriminate how collective information is displayed to users. We discuss the design implications informed by the results to shed light on the design of collective rating systems.
Year
DOI
Venue
2022
10.1145/3491102.3517726
Conference on Human Factors in Computing Systems
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
6
Name
Order
Citations
PageRank
Fu-Yin Cherng100.34
Jingchao Fang200.34
Yinhao Jiang300.34
Xi Chen433370.76
Taejun Choi500.34
Hao-Chuan Wang629645.80