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Towards Social Event Detection and Contextualisation for Journalists

Publication Type: 
Refereed Conference Meeting Proceeding
Abstract: 
Social media platforms have become an important source of information in course of a breaking news event, such as natural calamity, political uproar, etc. News organisations and journalists are increasingly realising the value of information being propagated via social media. However, the sheer volume of the data produced on social media is overwhelming and manual inspection of this streaming data for finding, aggregation, and contextualising emerging event in a short time span is a day-to-day challenge by journalists and media organisations. It highlights the need for better tools and methods to help them utilise this user generated information for news production. This paper addresses the above problem for journalists by proposing an event detection and contextualisation framework that receives an input stream of social media data and generates the likely events in the form of clusters along with a certain context.
Conference Name: 
25th International Conference on Computational Linguistics, August 2014 (COLING, 2014)
Proceedings: 
AHA! Workshop on Information Discovery in Text
Digital Object Identifer (DOI): 
10.NA
Publication Date: 
23/08/2014
Conference Location: 
Ireland
Research Group: 
Institution: 
National University of Ireland, Galway (NUIG)
Open access repository: 
Yes