Erschienen:
Association for the Advancement of Artificial Intelligence (AAAI), 2021
Erschienen in:
Proceedings of the International AAAI Conference on Web and Social Media, 6 (2021) 5, Seite 14-19
Sprache:
Nicht zu entscheiden
DOI:
10.1609/icwsm.v6i5.14216
ISSN:
2334-0770;
2162-3449
Entstehung:
Anmerkungen:
Beschreibung:
<jats:p>
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.
</jats:p>