What Kinds of Experiences Do You Desire? A Preliminary Study of the Desired Experiences of Contributors to Location-Based Mobile Crowdsourcing

Fang Yu Lin, Chia Yi Lee, Yi Ting Ho, Yao Kuang Chen, Grace Yu Chun Yen, Yung Ju Chang

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

Abstract

Mobile crowdsourcing enables people to learn location-related information from others with diverse experiences and opinions. However, little research has investigated the expected quality of the location-related information users of mobile-crowdsourcing platforms, and the levels and types of relevant experience such users expect crowd members to possess, respectively. To fill this gap, we first conducted an interview study with 22 participants, which yielded five key information properties of the answers to location-based questions: objectivity, relativity, specificity, temporal regularity, and variability. Based on his//her stated perceptions of these properties of the requested information, we deemed each participant to desire at least one, and up to 10 main qualities of the information, and seven main aspects of contributors' experience. A follow-up survey study was then used to quantify the characteristics of a list of location-related information according to the information properties that the 139 respondents perceived that information to have.

Original languageEnglish
Title of host publicationCHI 2022 - Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450391566
DOIs
StatePublished - 27 Apr 2022
Event2022 CHI Conference on Human Factors in Computing Systems, CHI EA 2022 - Virtual, Online, United States
Duration: 30 Apr 20225 May 2022

Publication series

NameConference on Human Factors in Computing Systems - Proceedings

Conference

Conference2022 CHI Conference on Human Factors in Computing Systems, CHI EA 2022
Country/TerritoryUnited States
CityVirtual, Online
Period30/04/225/05/22

Keywords

  • information quality
  • location-based
  • mobile crowdsourcing
  • review

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