Journal ArticleDOI
Tweet Analysis for Real-Time Event Detection and Earthquake Reporting System Development
Reads0
Chats0
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
More filters
Source profiling for smart city sensing
TL;DR: This thesis focuses on two types of sensing sources that have been used in smart city sensing projects, namely, environmental sensors and human sensors.
Proceedings ArticleDOI
EventPanorama: A Framework for Event Detection and Visualization from Online News
TL;DR: A hybrid event detection method which combines topic modeling and Chance Discovery, and detects events more effectively by coupling multiple term-relations is introduced and a heterogeneous event-graph layout algorithm is proposed which takes the significance of events into consideration by leveraging latent co-occurrence relations to represent important rare events and thus enhance human cognition.
Book ChapterDOI
Temporal Analysis of Comparative Opinion Mining
TL;DR: This study shows that temporal analysis of comparative opinion mining provides more current and relevant information to users compared to standard opinion mining.
Proceedings ArticleDOI
Lessons Learned from Event Detection from Arabic Tweets: The Case of Jordan Flash Floods near Dead Sea
Fatima B. Shannag,Bassam Hammo +1 more
TL;DR: This paper has used the Python Natural Language Toolkit (NLTK) library to develop two classifiers for filtering and detecting extracted events from Arabic tweets, and presents the tragic events of the Jordan flash floods near the Dead Sea.
Proceedings ArticleDOI
A Survey of Real-Time Social-Based Traffic Detection
TL;DR: In this article, the current state-of-the-art techniques in detecting traffic events in real-time focusing on seven papers [1], [2], [3], [4], [5], [6], [7] and [8] were surveyed.
References
More filters
Journal ArticleDOI
A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking
TL;DR: Both optimal and suboptimal Bayesian algorithms for nonlinear/non-Gaussian tracking problems, with a focus on particle filters are reviewed.
Journal ArticleDOI
The Computer for the 21st Century
TL;DR: Consider writing, perhaps the first information technology: The ability to capture a symbolic representation of spoken language for long-term storage freed information from the limits of individual memory.
Book ChapterDOI
Text Categorization with Suport Vector Machines: Learning with Many Relevant Features
TL;DR: This paper explores the use of Support Vector Machines for learning text classifiers from examples and analyzes the particular properties of learning with text data and identifies why SVMs are appropriate for this task.
Proceedings ArticleDOI
What is Twitter, a social network or a news media?
TL;DR: In this paper, the authors have crawled the entire Twittersphere and found a non-power-law follower distribution, a short effective diameter, and low reciprocity, which all mark a deviation from known characteristics of human social networks.
Journal Article
The computer for the 21st century
TL;DR: In this article, the authors propose that specialized elements of hardware and software, connected by wires, radio waves and infrared, will soon be so ubiquitous that no-one will notice their presence.