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Location-based crowdsourcing of hyperlocal news: dimensions of participation preferences

Published: 27 October 2012 Publication History

Abstract

We studied the mobile users' preferences and concerns of using location-based assignments (LBA) and geotagging in crowdsourced news making. First, nine readers who had submitted reader's photos were interviewed about their perceptions of LBA and geotagging scenarios. Second, a quasi-experiment in field conditions was carried out with nineteen participants. After completing four LBA tasks with a mobile phone, participants were interviewed on their perceptions and asked to complete a questionnaire on their preferences for receiving LBA and usage of geotags. Findings indicate that the perceived benefits of LBA and geotagging are greater than the perceived risks. The task type, temporal context, preciseness of location query, proximity to the reporting location, parallel tasks, social context and incentives affected the participation preferences. We propose a framework for participation preferences to support further studies in location-based crowdsourcing and in the development of crowdsourcing processes and systems.

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cover image ACM Conferences
GROUP '12: Proceedings of the 2012 ACM International Conference on Supporting Group Work
October 2012
342 pages
ISBN:9781450314862
DOI:10.1145/2389176
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 27 October 2012

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Author Tags

  1. assignment
  2. crowdsourcing
  3. location
  4. news
  5. privacy
  6. reader
  7. ugc

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October 27 - 31, 2012
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Overall Acceptance Rate 125 of 405 submissions, 31%

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  • (2024)Foresights for Location-Based Services in Media Management: Insights from an International Delphi StudyInternational Journal on Media Management10.1080/14241277.2024.238665525:3-4(115-145)Online publication date: 12-Sep-2024
  • (2021)A Blockchain-Based Spatial Crowdsourcing System for Spatial Information Collection Using a Reward DistributionSensors10.3390/s2115514621:15(5146)Online publication date: 29-Jul-2021
  • (2021)Local News and Geolocation Technology in the Case of PortugalPublications10.3390/publications90400539:4(53)Online publication date: 11-Nov-2021
  • (2020)Task Distribution Based on Variable-Order Markov Position Estimation in Mobile Sensor Networks2020 IEEE Symposium on Computers and Communications (ISCC)10.1109/ISCC50000.2020.9219630(1-7)Online publication date: Jul-2020
  • (2019)A Survey of Spatial CrowdsourcingACM Transactions on Database Systems10.1145/329193344:2(1-46)Online publication date: 15-Mar-2019
  • (2019)Motivations and habits of micro-news consumption on mobile social mediaTelematics and Informatics10.1016/j.tele.2019.10126244:COnline publication date: 1-Nov-2019
  • (2017)Designing for Targeted Responder ModelsProceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing10.1145/2998181.2998334(916-924)Online publication date: 25-Feb-2017
  • (2016)Crowdsourcing evolution: Towards a taxonomy of crowdsourcing initiatives2016 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops)10.1109/PERCOMW.2016.7457122(1-6)Online publication date: Mar-2016
  • (2015)Crowdsourcing in logisticsProceedings of the 17th International Conference on Information Integration and Web-based Applications & Services10.1145/2837185.2837242(1-8)Online publication date: 11-Dec-2015
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