Streaming Social Event Detection and Evolution Discovery in Heterogeneous Information Networks

Event Evolution Tracking from Streaming Social Posts

Online social post streams such as Twitter timelines and forum discussions have emerged as important channels for information dissemination. They are noisy, informal, and surge quickly. Real life events, which may happen and evolve every minute, are perceived and circulated in post streams by social users. Intuitively, an event can be viewed as a dense cluster of posts with a life cycle sharing...

Event Detection in Social Networks

Micro-blog services such as Twitter generate a large amount of messages carrying event information and users’ opinions over a wide range of topics. The events discussed on social networks can be associated with topics, locations, and time periods. The events can be a variety, such as celebrities or political affairs, local social events, accidents, protests, or natural disasters. Messages are p...

(Missing) Concept Discovery in Heterogeneous Information Networks

This article proposes a new approach to extract existing (or detect missing) concepts from a loosely integrated collection of information units by means of concept graph detection. Thereby a concept graph defines a concept by a quasi bipartite sub-graph of a bigger network with the members of the concept as the first vertex partition and their shared aspects as the second vertex partition. Once...

Outlier Detection Methodologies in Heterogeneous Information Networks

Event Analysis in Social Media Using Clustering of Heterogeneous Information Networks

In this paper, we propose a novel approach for social media event finding in order to support fast access to information that users find relevant. While there are many approaches related to this problem, they mainly focus on homogeneous data, such as either the text of the posts, or the network of users. Our research focuses on combining multiple types of data from social media in a heterogeneo...