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基于位置服务（Location-Based Services, LBS）依托智能设备的技术进步得以蓬勃发展。对基于位置的用户生成数据开展分析，是解析人类移动模式的有效路径，可进一步推动推荐系统、城市计算等各类应用的发展。在本数据描述文中，我们介绍由LBSLab采集的数据集：该系统是一款基于智能手机的微信小程序，专为在获取参与者知情同意的前提下，从其智能手机中大规模采集用户数据而设计。本次发布的数据集包含多类活动数据，涵盖登录、个人主页浏览、天气查询以及带有位置信息（经纬度）、POI（兴趣点，Point of Interest）和情绪标注的签到数据，采集自467名用户，时长共计11天。我们还提供了基础数据分析示例，期望该数据集的复用能够助力研究人员更深入地理解基于位置服务的用户行为、人类移动模式，以及人们情绪的时空分布特征。 如需了解LBSLab系统的更多详情，可查阅我们的相关研究论文：https://user.informatik.uni-goettingen.de/~ychen/papers/LBSLab-UbiComp18.pdf；亦可观看配套的YouTube视频：https://www.youtube.com/watch?v=m8r-1jqvYWc