App Usage Behavior Modeling and Prediction

The Tsinghua App Usage Dataset is a large-scale mobile application usage dataset collected over one week in one of China’s largest cities. It contains anonymized app usage logs from 1,000 users, capturing detailed information on 2,000 identified apps across 9,800 base stations. Each record includes user ID, timestamp, base station location, app ID, and traffic consumption, allowing for comprehensive analysis of individual and regional mobile usage patterns. This dataset has been widely applied in app usage behavior modeling, personalized app prediction, urban computing, and network traffic analysis. Previous research using this dataset has demonstrated key findings, such as the power-law distribution of app usage intervals, the high uniqueness of individual app usage patterns, and the strong correlation between app usage and location-based Points of Interest (PoIs). The dataset also provides essential metadata, including app category mapping, PoI distributions under each base station, and network traffic information, making it a valuable resource for mobile computing, recommendation systems, and human mobility studies. Researchers are encouraged to use the dataset for academic purposes while adhering to ethical guidelines prohibiting identity re-identification and commercial use.

清华应用使用数据集（Tsinghua App Usage Dataset）是一款大规模移动应用使用数据集，采集自中国一座特大城市，数据收集周期为一周。该数据集包含1000名用户的匿名化应用使用日志，覆盖9800个基站内的2000款已标识应用，并记录了详尽的相关信息。每条记录均包含用户ID、时间戳、基站位置、应用ID以及流量消耗情况，可支撑个体与区域级移动使用模式的全方位分析。该数据集已被广泛应用于应用使用行为建模、个性化应用预测、城市计算以及网络流量分析等领域。过往基于该数据集开展的研究已取得多项关键发现，例如应用使用间隔的幂律分布、个体应用使用模式的高度唯一性，以及应用使用行为与基于位置的兴趣点（Points of Interest, PoIs）之间的强相关性。该数据集还提供了关键元数据，包括应用类别映射表、各基站覆盖区域的兴趣点分布数据以及网络流量信息，是移动计算、推荐系统以及人类移动性研究领域的宝贵资源。鼓励研究人员将该数据集用于学术研究，但需遵守伦理准则，禁止进行身份重识别及商业用途。