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A human mobility dataset collected via LBSLab.

Yuwei Zhang1, Qingyuan Gong1, Yang Chen1

  • 1School of Computer Science, Fudan University, Shanghai 200433, China.

Data in Brief
|February 7, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a dataset of user activities from Location-Based Services (LBS) via the LBSLab WeChat mini-program. The data offers insights into human mobility patterns and user behaviors for recommender systems and urban computing.

Keywords:
Location-based servicesMobility dataMoodUser check-inWeather

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Area of Science:

  • Human-Computer Interaction
  • Data Science
  • Mobile Computing

Background:

  • Location-Based Services (LBS) leverage smart device technology for user activity analysis.
  • Understanding human mobility patterns is crucial for applications like recommender systems and urban computing.
  • User-generated data from LBS provides valuable insights into behavior and movement.

Purpose of the Study:

  • To document a dataset of user activities from a smartphone-based LBS system (LBSLab).
  • To provide data for analyzing human mobility patterns and user behaviors in LBS.
  • To enable research on the temporal and spatial characteristics of user moods.

Main Methods:

  • Collected activity data from 467 users over 11 days using the LBSLab system on WeChat.
  • Recorded user activities including logins, profile views, weather checks, and check-ins.
  • Included location data (latitude, longitude), Points of Interest (POI), and user-indicated moods.

Main Results:

  • The dataset comprises diverse user activities and associated location, POI, and mood information.
  • Temporal and spatial data analysis was performed on the collected user activity data.
  • The dataset captures nuanced user behaviors within Location-Based Services.

Conclusions:

  • The presented dataset facilitates deeper understanding of LBS user behaviors and human mobility.
  • Reuse of this data can advance research in recommender systems and urban computing.
  • The data allows for exploration of temporal and spatial mood variations in relation to LBS usage.