Name
Abstract | ||
|---|---|---|
Messages posted to social media in the aftermath of a natural disaster have value beyond detecting the event itself. Mining such deliberately dropped digital traces allows a precise situational awareness, to help provide a timely estimate of the disaster's consequences on the population and infrastructures. Yet, to date, the automatic assessment of damage has received little attention. Here, the a... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/MIC.2017.4180834 | IEEE Internet Computing |
Keywords | Field | DocType |
Earthquakes,Twitter,Sensors,Estimation,Tagging,Data mining | Data science,Population,World Wide Web,Social media,Predictive analytics,Situation awareness,Computer science,Social media mining,Natural disaster,Big data,Nowcasting | Journal |
Volume | Issue | ISSN |
21 | 6 | 1089-7801 |
Citations | PageRank | References |
3 | 0.36 | 17 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marco Avvenuti | 1 | 267 | 24.14 |
| Cresci, S. | 2 | 235 | 21.79 |
| Mariantonietta Noemi La Polla | 3 | 17 | 1.94 |
| Carlo Meletti | 4 | 49 | 2.11 |
| Maurizio Tesconi | 5 | 281 | 32.06 |