Name
Abstract | ||
|---|---|---|
Crowdsourcing is anticipated as a promising paradigm for Future of Work (FoW), where groups of humans are engaged for problem-solving, services and innovation which are usually difficult for machines. During the entire workflow of crowdsourcing, intensive interactions take place between workers and the crowdsourcing platform, as well as among groups of workers. For sustainable crowdsourcing, the design and management of these interactions should not regard human workers as machines, but rather as individuals and social beings. In this article, we highlight the critical interactions in typical crowdsourcing ecosystems, summarize past efforts on human-centric interaction management in crowdsourcing, and discuss emerging interaction management research towards cross-platform crowdsourcing. |
Year | Venue | DocType |
|---|---|---|
2019 | IEEE Data Eng. Bull. | Journal |
Volume | Issue | Citations |
42 | 4 | 0 |
PageRank | References | Authors |
0.34 | 0 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yansheng Wang | 1 | 7 | 2.52 |
| Tianshu Song | 2 | 13 | 3.89 |
| Qian Tao | 3 | 59 | 14.00 |
| Yuxiang Zeng | 4 | 48 | 6.06 |
| Zimu Zhou | 5 | 1157 | 61.40 |
| Yi Xu | 6 | 0 | 0.34 |
| Yongxin Tong | 7 | 1095 | 56.54 |
| Lei Chen | 8 | 6239 | 395.84 |