A4 Refereed article in a conference publication
User Motivations to Participate in Crowdsourcing and Contribute User-generated Content on Location-based Media: A Literature Review
Authors: Laato, Samuli; Siqueira, Sara; Baer, Manuel; Papangelis, Konstantinos; Kordyaka, Bastian; Nummenmaa, Timo; Hamari, Juho
Editors: Yamashita, Naomi; Evers, Vanessa; Yatani, Koji; Ding, Xianghua (Sharon); Lee, Bongshin; Chetty, Marshini; Toups-Dugas, Phoebe
Conference name: Conference on Human Factors in Computing Systems
Publisher: ACM
Publication year: 2025
Book title : CHI '25: Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems
Journal name in source: Conference on Human Factors in Computing Systems - Proceedings
First page : 1
Last page: 20
ISBN: 979-8-4007-1394-1
DOI: https://doi.org/10.1145/3706598.3714184
Web address : https://doi.org/10.1145/3706598.3714184
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/498487360
Location-based media applications such as Google Maps, Strava and Pokémon GO together have more than a billion monthly active users, and popular social media such as Snapchat and Instagram now also feature map-based content. All these media products rely on user-generated content as a core element of their service, but there is a lack of synthesis on the users' motivations to contribute this data to the platform providers. In this study, we performed a literature review to uncover users' motivations to participate in location-based crowdsourcing and contribute shared content on these platforms. Among our findings, we show that spatial and temporal aspects, social effects, technical elements, motivational mechanisms, practical value offered to the contributors and individual differences need to be considered in motivating users to contribute shared content. We present recommendations for designers, suggest which terminology to use around this topic and propose an agenda for future research.
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Funding information in the publication:
This work was supported by the Research Council of Finland Flagship Programme UNITE (Grant number 357907), the Research Council of Finland -funded GamiLiDAR project (Grant number 359472) and the Swiss National Science Foundation SNSF (Grant number 214436).
