  Customer product reviews play a role in improving the quality of products and
services for organizations or brands. Complaining is an attitude that expresses
dissatisfaction with an event or a product not meeting customer expectations.
In this paper, we build a Vietnamese dataset (UIT-ViOCD), including 5,485
human-annotated reviews on four categories about product reviews on e-commerce
sites. After the data collection phase, we proceed to the annotation task and
achieve Am = 87% by Fleiss' Kappa. Then, we present an extensive methodology
for the research purposes and achieve 92.16% by F1-score for identifying
complaints. With the results, in the future, we want to build a system for
open-domain complaint detection in E-commerce websites.
