| Title |
A framework for detecting unfolding emergencies using humans as sensors
|
|---|---|
| Published in |
SpringerPlus, January 2016
|
| DOI | 10.1186/s40064-016-1674-y |
| Pubmed ID | |
| Authors |
Marco Avvenuti, Mario G. C. A. Cimino, Stefano Cresci, Andrea Marchetti, Maurizio Tesconi |
| Abstract |
The advent of online social networks (OSNs) paired with the ubiquitous proliferation of smartphones have enabled social sensing systems. In the last few years, the aptitude of humans to spontaneously collect and timely share context information has been exploited for emergency detection and crisis management. Apart from event-specific features, these systems share technical approaches and architectural solutions to address the issues with capturing, filtering and extracting meaningful information from data posted to OSNs by networks of human sensors. This paper proposes a conceptual and architectural framework for the design of emergency detection systems based on the "human as a sensor" (HaaS) paradigm. An ontology for the HaaS paradigm in the context of emergency detection is defined. Then, a modular architecture, independent of a specific emergency type, is designed. The proposed architecture is demonstrated by an implemented application for detecting earthquakes via Twitter. Validation and experimental results based on messages posted during earthquakes occurred in Italy are reported. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 71 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Philippines | 1 | 1% |
| Ireland | 1 | 1% |
| Unknown | 69 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 19 | 27% |
| Student > Master | 16 | 23% |
| Professor > Associate Professor | 6 | 8% |
| Researcher | 5 | 7% |
| Student > Postgraduate | 3 | 4% |
| Other | 8 | 11% |
| Unknown | 14 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 23 | 32% |
| Social Sciences | 8 | 11% |
| Earth and Planetary Sciences | 5 | 7% |
| Engineering | 5 | 7% |
| Nursing and Health Professions | 2 | 3% |
| Other | 10 | 14% |
| Unknown | 18 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 March 2016.
All research outputs
#4,027,071
of 22,842,950 outputs
Outputs from SpringerPlus
#241
of 1,849 outputs
Outputs of similar age
#70,466
of 394,468 outputs
Outputs of similar age from SpringerPlus
#17
of 210 outputs
Altmetric has tracked 22,842,950 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,849 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one has done well, scoring higher than 86% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 394,468 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 210 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.