Name
Title | ||
|---|---|---|
Image-based Social Sensing: Combining AI and the Crowd to Mine Policy-Adherence Indicators from Twitter |
Abstract | ||
|---|---|---|
Social Media provides a trove of information that, if aggregated and analysed appropriately can provide important statistical indicators to policy makers. In some situations these indicators are not available through other mechanisms. For example, given the ongoing COVID-19 outbreak, it is essential for governments to have access to reliable data on policy-adherence with regards to mask wearing, s... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ICSE-SEIS52602.2021.00019 | 2021 IEEE/ACM 43rd International Conference on Software Engineering: Software Engineering in Society (ICSE-SEIS) |
Keywords | DocType | ISBN |
COVID-19,Social networking (online),Pipelines,Social factors,Sensors,Software reliability,Software engineering | Conference | 978-1-6654-0139-5 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Virginia Negri | 1 | 0 | 0.34 |
| Dario Scuratti | 2 | 0 | 0.34 |
| Stefano Agresti | 3 | 0 | 0.34 |
| Donya Rooein | 4 | 0 | 0.68 |
| Amudha Ravi Shankar | 5 | 0 | 1.01 |
| Jose Luis Fernandez Marquez | 6 | 0 | 0.34 |
| Mark James Carman | 7 | 5 | 1.51 |
| Barbara Pernici | 8 | 3401 | 488.75 |