CRAWDAD telefonica/mobilephoneuse

Citation Author(s):
Martin
Pielot
Telefonica Research
Submitted by:
CRAWDAD Team
Last updated:
Mon, 04/29/2019 - 08:00
DOI:
10.15783/jh3s-h006
Data Format:
License:
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Collection:
CRAWDAD
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Abstract 

Detailed mobile phone use data (events, sensors, emotion self-reports, traits) of 342 people over the course of 342

Detailed logs of mobile phone usage of 342 people over the course of ca. 4 weeks. Contains events from 25 physical and virtual sensors (e.g. app in foreground, received notifications, ambient noise level, semantic location, ...), frequent self reports of emotions (valence and arousal), and for some participants self-reported traits (Big 5 Traits, Boredom Proneness [BPS], Patient Health Questionnaire [PHQ8]). Sensors: acceleration, airplane mode, app in foreground, audio, battery, battery drain, cell tower details, data consumption, ambient light, ambient noise, notifications, notification center access, notification dismissed, notifications cleared, device orientation, phone calls, photos, proximity (screen covered or not), screen events (on, off, unlocked), screen orientation (portrait, landscape), semantic location (home, work, ...), sms events, user activity (sitting, in vehicle, ...), wifi details. Details can be found at https://sites.google.com/view/mobile-phone-use-dataset

last modified : 2019-04-29

nickname : mobilephoneuse

institution : telefonica

release date : 2019-04-29

date/time of measurement start : 2016-04-15

date/time of measurement end : 2016-07-12

collection environment : 342 mobile phone users recruited by an agency to match the demographics of the country of study: Spain

Traceset

telefonica/mobilephoneuse/MobilePhoneUse

Detailed mobile phone use data (events, sensors, emotion self-reports, traits) of 342 people over the course of 342

  • files: mpu.zip
  • description: Detailed logs of mobile phone usage of 342 people over the course of ca. 4 weeks. Contains events from 25 physical and virtual sensors (e.g. app in foreground, received notifications, ambient noise level, semantic location, ...), frequent self reports of emotions (valence and arousal), and for some participants self-reported traits (Big 5 Traits, Boredom Proneness [BPS], Patient Health Questionnaire [PHQ8]). Sensors: acceleration, airplane mode, app in foreground, audio, battery, battery drain, cell tower details, data consumption, ambient light, ambient noise, notifications, notification center access, notification dismissed, notifications cleared, device orientation, phone calls, photos, proximity (screen covered or not), screen events (on, off, unlocked), screen orientation (portrait, landscape), semantic location (home, work, ...), sms events, user activity (sitting, in vehicle, ...), wifi details. Details can be found at https://sites.google.com/view/mobile-phone-use-dataset
  • measurement purpose: Usage Characterization, Human Behavior Modeling
  • methodology: This data was collected as part of a dedicated study. Volunteers installed an application onto their phones to collect a wide range of mobile phone use events, sensor data, and self-reports.
Instructions: 

The files in this directory are a CRAWDAD dataset hosted by IEEE DataPort. 

About CRAWDAD: the Community Resource for Archiving Wireless Data At Dartmouth is a data resource for the research community interested in wireless networks and mobile computing. 

CRAWDAD was founded at Dartmouth College in 2004, led by Tristan Henderson, David Kotz, and Chris McDonald. CRAWDAD datasets are hosted by IEEE DataPort as of November 2022. 

Note: Please use the Data in an ethical and responsible way with the aim of doing no harm to any person or entity for the benefit of society at large. Please respect the privacy of any human subjects whose wireless-network activity is captured by the Data and comply with all applicable laws, including without limitation such applicable laws pertaining to the protection of personal information, security of data, and data breaches. Please do not apply, adapt or develop algorithms for the extraction of the true identity of users and other information of a personal nature, which might constitute personally identifiable information or protected health information under any such applicable laws. Do not publish or otherwise disclose to any other person or entity any information that constitutes personally identifiable information or protected health information under any such applicable laws derived from the Data through manual or automated techniques. 

Please acknowledge the source of the Data in any publications or presentations reporting use of this Data. 

Citation:

Martin Pielot, telefonica/mobilephoneuse, https://doi.org/10.15783/jh3s-h006 , Date: 20190429

Dataset Files

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These datasets are part of Community Resource for Archiving Wireless Data (CRAWDAD). CRAWDAD began in 2004 at Dartmouth College as a place to share wireless network data with the research community. Its purpose was to enable access to data from real networks and real mobile users at a time when collecting such data was challenging and expensive. The archive has continued to grow since its inception, and starting in summer 2022 is being housed on IEEE DataPort.

Questions about CRAWDAD? See our CRAWDAD FAQ. Interested in submitting your dataset to the CRAWDAD collection? Get started, by submitting an Open Access Dataset.