Combining participatory and ESM: A hybrid approach to collecting annotated mobility data

Hsiu Chi Chang, Yung-Ju Chang, Mark W. Newman, Chih Hsin Lin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Collecting continual labeled activity data entails considerable effort from users to label a series of activity data. We propose Checkpoint-and-Remind (CAR), a hybrid approach that combines participatory (PART) and context-trigger ESM labeling (ESM). Checkpoint-and-Remind has the advantage of user control but reduces users' burden in recording activities. Meanwhile, it features a context-trigger mechanism of ESM as a backup to remind users of labeling. Our preliminary evaluation of CAR with nine participants, who collected and labeled their mobility activity data for 15 weekdays, showed that compared with PART and ESM, participants collected a larger amount of annotated mobility data using CAR. In addition, participants had a higher annotation rate when using CAR than when using ESM. Our results show that the hybrid approach that combines manual and automated recording is promising. Our future work is validating these results and measure more metrics related to compliance with more participants.

Original languageEnglish
Title of host publicationCHI EA 2020 - Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450368193
DOIs
StatePublished - 25 Apr 2020
Event2020 ACM CHI Conference on Human Factors in Computing Systems, CHI EA 2020 - Honolulu, United States
Duration: 25 Apr 202030 Apr 2020

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Conference

Conference2020 ACM CHI Conference on Human Factors in Computing Systems, CHI EA 2020
CountryUnited States
CityHonolulu
Period25/04/2030/04/20

Keywords

  • Activity collection
  • Annotation
  • Field experiment
  • Ground truth
  • Label
  • Transportation
  • Wearable camera

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