DocumentCode :
3587546
Title :
Location identification for crime & disaster events by geoparsing Twitter
Author :
Dhavase, Nikhil ; Bagade, A.M.
Author_Institution :
Dept. of Inf. Technol., Pune Inst. of Comput. Technol., Pune, India
fYear :
2014
Firstpage :
1
Lastpage :
3
Abstract :
Geoparsing means automatically identifying locations in text. The location mentions in messages during crime and disaster events are very crucial, as they can help emergency response teams to quickly identify the place to send rescue teams to the location. Use of social media during such crisis events has been rapidly increasing all over the world, as well as in India. We consider here the source of messages as Twitter because it is realtime, robust and can handle large amounts of data. We collect tweets at real time and then parse those tweets for crisis situation and location information. Extracting the location information to the level of streets & buildings will help to detect the exact location of the event; this is done with the help of NLP methods. We use classifiers to classify tweets to obtain the event occurred.
Keywords :
disasters; grammars; natural language processing; program compilers; social networking (online); NLP methods; Twitter; crime events; crisis situation; disaster events; emergency response teams; geoparsing; location identification; real time; rescue teams; social media; Buildings; Conferences; Data mining; Event detection; Media; Real-time systems; Twitter; Geoparsing; Twitter; disaster response management; event classification; geographic information retrieval;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Convergence of Technology (I2CT), 2014 International Conference for
Print_ISBN :
978-1-4799-3758-5
Type :
conf
DOI :
10.1109/I2CT.2014.7092336
Filename :
7092336
Link To Document :
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