Work

Mapping Community Engagement with Urban Crowd-Sourcing

Year: 2021

Type: conference-paper

Abstract: Cities are highly dynamic entities, with urban elements such as businesses, cultural and social Points-of- Interests (POIs), housing, transportation and the like, continuously changing. In order to maintain accurate spatial information in these settings, crowd-sourcing models of data collection, such as in OpenStreetMap (OSM), have come under investigation. Like many crowd-sourcing platforms (e.g., Wikipedia), these geo- wikis exhibit tailing-off activity, bringing into ques- tion their long-term viability. In this paper, we begin an investigation into the sustainability of urban crowd-sourcing, by studying the network structure and ge- ographical mapping of implicit communities of con- tributors in OSM. We observe that spatially clustered crowd-sourcing communities produce higher coverage than those with looser geographic affinity. We discuss the positive implications that this has on the future of urban crowd-sourcing.

Source: Proceedings of the International AAAI Conference on Web and Social Media

DOI: 10.1609/icwsm.v6i5.14216

Authors: Desislava Hristova, Afra Mashhadi, Giovanni Quattrone, Licia Capra

Institution: University College London

Language: English

Topic: Geographic Information Systems Studies

Subfield: Geography, Planning and Development

Field: Social Sciences

Domain: Social Sciences

SDG: Sustainable cities and communities

Open Access status: diamond

Funder: European Commission