Name
Abstract | ||
|---|---|---|
Social networks like twitter reveals a lot of what is going on around in a city. Posts and tweets of people visiting events, concerts or attending civil demonstrations are on the norm of social networks. By mining such data, social networks can reveal the hotspots of events or activities demonstrating the pulse of a Smart City in real time. This paper presents the current state of the art in the field of event detection in social networks. After covering the basics of event detection, we present several selected publications covering diverse approaches, pointing out their advantages and limitations. We further identify open research gaps presenting our current efforts towards a more robust and complete event detection technique. |
Year | Venue | Field |
|---|---|---|
2017 | iThings/GreenCom/CPSCom/SmartData | Data science,Open research,Anomaly detection,Social network,Computer science,Norm (social),Smart city |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| julio de melo borges | 1 | 8 | 3.24 |
| Peter Bozsoky | 2 | 0 | 0.34 |
| Simon Sudrich | 3 | 1 | 1.02 |
| M. Beigl | 4 | 2034 | 311.09 |