We investigate the characteristics of location review texts written on the basis of actual visit experiences or without any visit experiences. Specifically, we formalize this as a binary classification task and propose a data construction framework that labels reviews as Visit or NotVisit by linking them with users’ GPS-based movement data. We train a logistic regression model on the dataset and evaluate it alongside human annotators and a large language model (LLM). The results show that the task is more challenging for humans and LLMs than for the simple trained model.