Disaster Reporting and Alert System Using Tweets in Social Media
P.Tamije Selvy1, V. Suriya Prakash2, S. Shriram3, N. Vimalesh4, M. Anitha5
1Dr. P. Tamije Selvy, Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, (Tamil Nadu), India.
2V. Suriya Prakash, Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, (Tamil Nadu), India.
3S.Shriram, Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, (Tamil Nadu), India.
4N.Vimalesh, Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, (Tamil Nadu), India.
5M.Anitha, Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, (Tamil Nadu), India.
Manuscript received on 23 March 2019 | Revised Manuscript received on 30 March 2019 | Manuscript published on 30 March 2019 | PP: 1245-1249 | Volume-7 Issue-6, March 2019 | Retrieval Number: F3007037619/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Social media is one of the powerful micro blogging platforms which is used to express the wide range of thoughts by an individual. Since this type of vast data is pretty much helpful to bring various applications. The pre-existed model does not comprise dynamic data generated by the user, but this model is programmed in a way to extract the dynamic data that is generated by various users. This proposed model investigates the real-time interaction of events such as earthquakes, tsunami, etc., in social media and proposes an algorithm to monitor hashtags and to report disaster. The model reports a disaster and gives alert to the users residing in the disaster location using the words in the posts relating the disaster event, number of words, and their context. The model considers each hash tags as an input and applies semantic analysis, which is widely used for estimation of consequences. Because of the numerous disasters and large number of Social media users throughout the country, this proposed system can report disaster more accurately by monitoring hashtags. The model reports natural disasters give alert to the users and also represent it visually.
Keywords: Micro Blogging, User tweets, Twitter.
Scope of the Article: Social Networks