Name
Abstract | ||
|---|---|---|
People are using social media to a greater extent, particularly in emergency situations. However, approaches for processing and analyzing the vast quantities of data produced currently lag far behind. In this paper we discuss important steps, and the associated challenges, for processing and analyzing social media in emergencies. In our research project EmerGent, a huge volume of low-quality messages will be continuously gathered from a variety of social media services such as Facebook or Twitter. Our aim is to design a software system that will process and analyze social media data, transforming the high volume of noisy data into a low volume of rich content that is useful to emergency personnel. Therefore, suitable techniques are needed to extract and condense key information from raw social media data, allowing detection of relevant events and generation of alerts pertinent to emergency personnel. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/ICT-DM.2015.7402055 | 2015 2nd International Conference on Information and Communication Technologies for Disaster Management (ICT-DM) |
Keywords | Field | DocType |
social media,information gathering,information mining,ontology,emergency services,emergencies,information quality,information visualisation | Ontology (information science),Noisy data,World Wide Web,Data stream mining,Social media,Social media optimization,Computer science,Software system,Semantics | Conference |
ISSN | Citations | PageRank |
2469-8822 | 5 | 0.43 |
References | Authors | |
26 | 8 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Matthias Moi | 1 | 5 | 0.77 |
| Therese Friberg | 2 | 8 | 1.49 |
| Robin Marterer | 3 | 6 | 1.80 |
| Christian Reuter | 4 | 214 | 47.92 |
| Thomas Ludwig | 5 | 72 | 21.48 |
| Deborah Markham | 6 | 5 | 0.77 |
| Mike Hewlett | 7 | 5 | 0.43 |
| Andrew Muddiman | 8 | 5 | 1.11 |