Name
Abstract | ||
|---|---|---|
A social event is an occurrence that involves lots of people and is accompanied by an obvious rise in human flow. Analysis of social events has real-world importance because events bring about impacts on many aspects of city life. Traditionally, detection and impact measurement of social events rely on social investigation, which involves considerable human effort. Recently, by analyzing messages in social networks, researchers can also detect and evaluate country-scale events. Nevertheless, the analysis of city-scale events has not been explored. In this article, we use human flow dynamics, which reflect the social activeness of a region, to detect social events and measure their impacts. We first extract human flow dynamics from taxi traces. Second, we propose a method that can not only discover the happening time and venue of events from abnormal social activeness, but also measure the scale of events through changes in such activeness. Third, we extract traffic congestion information from traces and use its change during social events to measure their impact. The results of experiments validate the effectiveness of both the event detection and impact measurement methods. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1145/2700478 | ACM Transactions on Intelligent Systems and Technology |
Keywords | Field | DocType |
Algorithms,Performance,Social event,social impact,traffic condition,taxi traces | Social network,Social event detection,Computer security,Computer science,Social impact,Traffic conditions,Traffic congestion | Journal |
Volume | Issue | ISSN |
6 | 3 | 2157-6904 |
Citations | PageRank | References |
17 | 0.71 | 21 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wangsheng Zhang | 1 | 205 | 8.85 |
| Guande Qi | 2 | 418 | 19.45 |
| Gang Pan | 3 | 1501 | 123.57 |
| Hua Lu | 4 | 1380 | 83.74 |
| Shijian Li | 5 | 1155 | 69.34 |
| Zhaohui Wu | 6 | 3121 | 246.32 |