DocumentCode
261018
Title
Social data analysis for predicting next event
Author
Deiva Ragavi, M. ; Usharani, S.
Author_Institution
Dept. of CSE, Anna Univ., Chennai, India
fYear
2014
fDate
27-28 Feb. 2014
Firstpage
1
Lastpage
5
Abstract
Twitter is a user-friendly social network which deserves its real-time nature. With the help of an algorithm, the investigation can be made with regard to some of the real-time events such as earthquake. The target event is assumed and classified based on the keywords, number of words and their context. The probabilistic spatiotemporal model is provided which can find the Centre of the event location. The Twitter users are regarded as sensors and apply particle filter, mainly used for detecting the location. Because of the numerous earthquakes and the large number of Twitter users throughout the country, we can detect an earthquake with high probability merely by monitoring tweets. Our system detects earthquakes promptly and notification much faster than JMA (Japan Meteorological Agency) broadcast announcements.
Keywords
earthquakes; geophysics computing; human computer interaction; particle filtering (numerical methods); probability; real-time systems; social networking (online); JMA; Japan Meteorological Agency broadcast announcement; Twitter; earthquakes; event location; location detection; monitoring tweets; particle filter; probabilistic spatiotemporal model; probability; real-time events; real-time nature; social data analysis; user-friendly social network; Earthquakes; Educational institutions; Electronic mail; Event detection; Real-time systems; Sensors; Twitter; Data Mining; Social Data; Social Media; Text Mining; Tweets; Twitter; earthquake; event detection; social sensor;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Communication and Embedded Systems (ICICES), 2014 International Conference on
Conference_Location
Chennai
Print_ISBN
978-1-4799-3835-3
Type
conf
DOI
10.1109/ICICES.2014.7033935
Filename
7033935
Link To Document