Publikation: Getting there first : real-time detection of real-world incidents on Twitter
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2012
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Zusammenfassung
Social networking and micro-blogging services such as Twitter have become a valuable source of information on current events. Widespread use of Twitter on mobile devices and personal computers enables users to share short messages on any subject in real-time, thus making it suitable for early detection of unexpected events where fast response is critical. In this paper, we present an online method for detection of real-world events in Twitter data, such as natural disasters or man-made catastrophes, by analyzing Twitter data. Our method combines different textual and frequency components that represent or approximate interesting semantic aspects of an event. We use visualization as a validation vehicle, which allows us to understand which components are relevant and what impact the parameters have on the results of our event detection algorithm.
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KRSTAJIC, Milos, Christian ROHRDANTZ, Michael BLUMENSCHEIN, Andreas WEILER, 2012. Getting there first : real-time detection of real-world incidents on TwitterBibTex
@inproceedings{Krstajic2012Getti-22949,
year={2012},
title={Getting there first : real-time detection of real-world incidents on Twitter},
author={Krstajic, Milos and Rohrdantz, Christian and Blumenschein, Michael and Weiler, Andreas},
note={2nd Workshop on Interactive Visual Text Analytics : Task-Driven Analysis of Social Media Content with Visweek’12.<br /> Oct. 2012.}
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<dcterms:abstract xml:lang="eng">Social networking and micro-blogging services such as Twitter have become a valuable source of information on current events. Widespread use of Twitter on mobile devices and personal computers enables users to share short messages on any subject in real-time, thus making it suitable for early detection of unexpected events where fast response is critical. In this paper, we present an online method for detection of real-world events in Twitter data, such as natural disasters or man-made catastrophes, by analyzing Twitter data. Our method combines different textual and frequency components that represent or approximate interesting semantic aspects of an event. We use visualization as a validation vehicle, which allows us to understand which components are relevant and what impact the parameters have on the results of our event detection algorithm.</dcterms:abstract>
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Kommentar zur Publikation
2nd Workshop on Interactive Visual Text Analytics : Task-Driven Analysis of Social Media Content with Visweek’12.
Oct. 2012.
Oct. 2012.
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Ja
