Event detection on large social media using temporal analysis
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Authors
Aldhaheri, Abdulrahman
Issue Date
2017-03-24
Type
Presentation
Language
en_US
Keywords
Event detection , Machine learning , Social media
Alternative Title
Abstract
The problem of event detection based on social media has attracted researchers’ attention recently because of the enormous popularity of social media. Existing approaches focus on features that don’t reflect full characteristics of the social network. For the purpose of this research, we define an event as an occurrence that has enough force and momentum that could create an observable change of the context of a social network. Such a definition provides us with a wider perspective through which we can view the big picture of the social network. In this research, we propose a novel framework for detecting events on social media. We introduce a temporal approach to detect structural change of the social network that reflects an occurrence of an event using machine learning algorithms. In this study, we show that processing temporal social networks captures the complete complexity of the social network, which results in a higher accuracy of event detection.