[u" @inproceedings{klein_detection_2012, address = {Berlin, Heidelberg}, series = {{UCAmI}'12}, title = {Detection and extracting of emergency knowledge from twitter streams}, isbn = {978-3-642-35376-5}, url = {http://dx.doi.org/10.1007/978-3-642-35377-2_64}, doi = {10.1007/978-3-642-35377-2_64}, abstract = {Increasingly, more important information is being shared through Twitter. New opportunities arise to use this tool to detect emergencies and extract crucial information about the scope and nature of that event. A major challenge for the extraction of emergency event information from Twitter is represented by the unstructured and noisy nature of tweets. Within the SABESS project we propose a combined structural and content based analysis approach. We use social network analysis to identify reliable tweets and content analysis techniques to summarize key emergency facts.}, urldate = {2013-09-23TZ}, booktitle = {Proceedings of the 6th international conference on {Ubiquitous} {Computing} and {Ambient} {Intelligence}}, publisher = {Springer-Verlag}, author = {Klein, Bernhard and Laiseca, Xabier and Casado-Mansilla, Diego and L\xf3pez-de-Ipi\xf1a, Diego and Nespral, Alejandro Prada}, year = {2012}, keywords = {Twitter, emergency detection, natural language processing, sabess, social network analysis}, pages = {462--469} }"]