A Human Mobility Dataset Collected via LBSLab

Location-Based Services (LBS) have been prosperous owing to technological advancements of smart devices. Analyzing location based user generated data is a helpful way to understand human mobility patterns, further fueling applications such as recommender systems and urban computing. In this data descriptor, we introduce a dataset collected by LBSLab, a smartphone-based system implemented as a mini-program in the WeChat app, designed for large scale data collection from the smartphones of the participants with their informed consent. We provide activity data of multiple types including logins, profile viewing, weather checking, and check-ins with location information (latitude and longitude), POI and mood indicated, collected from 467 users over a duration of 11 days. We present some basic data analysis and expect the reuse of the data will allow researchers to better understand user behaviors of LBSs, human mobility, and also temporal and spatial characteristics of people’s mood.<br>For further information about the LBSLab system, you can check out our position paper here: https://user.informatik.uni-goettingen.de/~ychen/papers/LBSLab-UbiComp18.pdf<br>And also the Youtube video here: https://www.youtube.com/watch?v=m8r-1jqvYWc

搜集汇总

背景与挑战

背景概述

该数据集通过微信小程序LBSLab收集，包含467名用户在11天内的活动数据，如登录、签到等，并附带位置信息、POI和情绪指示。它旨在支持人类移动模式、位置服务用户行为及情绪时空特征的研究，适用于文化地理和移动计算领域。