Powering the local review engine at Yelp and Google: intensive and extensive approaches to crowdsourcing spatial data
研究了Yelp和Google Maps如何通过志愿者顶级贡献者项目确保可靠空间数据，Yelp采用集约式精英小队模式，Google采用广延式本地向导模式，两者以不同方式激励用户无偿贡献。
This paper explores how two major location-based services in the United States, Yelp and Google Maps, use volunteer top-contributor programmes to ensure access to reliable spatial data. Through the Elite Squad programme, paid Yelp staff take an active curatorial role growing the company’s reviewer base in select urban regions in North America. Google’s Local Guides programme uses an extensive, self-service model to collect data on a global scale. Both companies enrol and motivate users in ways that present unpaid review labour as affirming, with emphases that reflect their scalar strategies: Yelp stressing tight-knit sociality and Google global altruism.