From event detection to storytelling on microblogs

Janani Kalyanam, Sumithra Velupillai, Mike Conway, Gert Lanckriet

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

The problem of detecting events from content published on microblogs has garnered much interest in recent times. In this paper, we address the questions of what happens after the outbreak of an event in terms of how the event gradually progresses and attains each of its milestones, and how it eventually dissipates. We propose a model based approach to capture the gradual unfolding of an event over time. This enables the model to automatically produce entire timeline trajectories of events from the time of their outbreak to their disappearance. We apply our model on the Twitter messages collected about Ebola during the 2014 outbreak and obtain the progression timelines of several events that occurred during the outbreak. We also compare our model to several existing topic modeling and event detection baselines in literature to demonstrate its efficiency.

Original languageEnglish
Title of host publicationProceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016
EditorsRavi Kumar, James Caverlee, Hanghang Tong
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages437-442
Number of pages6
ISBN (Electronic)9781509028467
DOIs
StatePublished - Nov 21 2016
Externally publishedYes
Event2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016 - San Francisco, United States
Duration: Aug 18 2016Aug 21 2016

Publication series

NameProceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016

Conference

Conference2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2016
Country/TerritoryUnited States
CitySan Francisco
Period08/18/1608/21/16

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