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projects:year1:12.1

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12.1 - Social Media for Decision Informatics with Application to Emerging Events

Project - Summary

Objectives:

The objective of this project was to detect the onset of events using social media, especially twitter streams. To accomplish this, we (a) developed a new method to detect the onset of events, (b) studied topic evolution, which takes unstructured time stamped data as input and identify, in an unsupervised manner, the latent topics and how these topics evolve and © generate a simplistic visualization of the arrival tweets.

Project - Team

Team Member Role Email Phone Number Academic Site/IAB
Ryan G. Benton PI Not available Not available UL Lafayette
Chaomei Chen Site Coordinator Not available Not available Drexel Univeristy
Jian Chen Co-PI Not available Not available UL Lafayette
Raju Gottumukkala Co-PI Not available Not available UL Lafayette
Wanying Ding Graduate Student Not available Not available Drexel University
Satya Katragadda Graduate Student Not available Not available UL Lafayette
Sonal Pardeshi Graduate Student Not available Not available Drexel University
Shahid Virani Graduate Student Not available Not available UL Lafayette

Project - Impact and Uses/Benefits

Onset Event Detection The EDO method could, for Emergency Event Managemers, provide advanced warning (or confirmation) of disasters/emergencies. In the case of advanced warning, this allows them to react in a more timely fashion, while, in the confirmation mode, it allows them to gauge potential impact. This could also be of use to news organizations, who often need to know what are new, potentially interesting (or news worthy) stories.

Topic Modeling Currently, there is no evidence except the comparative study.

Project - Deep Dive

Project - Documents

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projects/year1/12.1.1566424100.txt.gz · Last modified: 2019/08/21 16:48 by sally.johnson