Event Analysis in Social Media using Clustering of Heterogeneous Information Networks
Refereed Conference Meeting Proceeding
In this paper, we propose a novel approach for clustering social media events in order to support easy access to information that users find relevant. While there are many approaches related to this problem, they mainly focus on homogeneous data, such as text of the posts or a network of users at a time. Our research focuses on combining multiple types of data from social media in heterogeneous network. We propose different graph- based models using users, posts, and concepts extracted from Tweet text to represent social media network and group posts by different topics and events by analyz- ing this heterogeneous network. Our preliminary results show improvement over the method which typically uses one type of data.
The 28th International FLAIRS Conference
Digital Object Identifer (DOI):
United States of America
National University of Ireland, Galway (NUIG)
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