Journal ArticleDOI
Tweet Analysis for Real-Time Event Detection and Earthquake Reporting System Development
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TLDR
An earthquake reporting system for use in Japan is developed and an algorithm to monitor tweets and to detect a target event is proposed, which produces a probabilistic spatiotemporal model for the target event that can find the center of the event location.Abstract:
Twitter has received much attention recently. An important characteristic of Twitter is its real-time nature. We investigate the real-time interaction of events such as earthquakes in Twitter and propose an algorithm to monitor tweets and to detect a target event. To detect a target event, we devise a classifier of tweets based on features such as the keywords in a tweet, the number of words, and their context. Subsequently, we produce a probabilistic spatiotemporal model for the target event that can find the center of the event location. We regard each Twitter user as a sensor and apply particle filtering, which are widely used for location estimation. The particle filter works better than other comparable methods for estimating the locations of target events. As an application, we develop an earthquake reporting system for use in Japan. Because of the numerous earthquakes and the large number of Twitter users throughout the country, we can detect an earthquake with high probability (93 percent of earthquakes of Japan Meteorological Agency (JMA) seismic intensity scale 3 or more are detected) merely by monitoring tweets. Our system detects earthquakes promptly and notification is delivered much faster than JMA broadcast announcements.read more
Citations
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Journal ArticleDOI
Optimizing disaster communication for future fire mitigation
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TL;DR: In this article , the authors used the descriptive-analytic method to identify the research area and collect secondary data to find out how to optimize disaster communication for future fire mitigation in Kalimantan.
Proceedings ArticleDOI
Extracting Large Scale Spatio-Temporal Descriptions from Social Media
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Real-Time Detection of Traff ic From Twitter Stream Analysis
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Journal ArticleDOI
Analyzing Events’ Impacts on Mental Health Using Tweets
TL;DR: In this article , the effect of cyclones, bomb blasts, and earthquakes on people's mental health was analyzed using the area under the curve (AUC) method to mine the tweets.
References
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