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A Survey on Event Detection in Social Networks
PhD Qualifying Examination
Title: "A Survey on Event Detection in Social Networks"
by
Miss Jieying SHE
Abstract:
A diversity of social network platforms, such as Twitter and Facebook, are
becoming popular in recent years. Thanks to the easiness of publishing and
spreading information on these platforms, users can report instant news or
emergencies and others can follow up or help spread the related messages.
People can learn about certain events even more instantly on these
platforms than on traditional news media platforms. However, due to the
huge number of messages generated every second in these social networks,
manually monitoring any instant event is costly and infeasible.
Researchers have been exploring automatic event detection solutions for
these platforms.
Automatic event detection in social networks is however non-trivial and
challenging. In addition to the data amount on these platforms that urges
for highly efficient algorithms, the noise of data requires event
detection solutions to effectively distinguish event-relevant messages
from a large number of spam or event-irrelevant ones.
In this survey, we first introduce the motivation of studying automatic
event detection in social networks. We compare how different event
detection is in modern social networks than in traditional media, and
clarify why this research topic is challenging. We then review current
event detection techniques applied to social network platforms.
Particularly, we focus on event detection on Twitter, a social media
platform that draws most attention from researchers because of its
popularity among users in reporting instant events and the challenges it
brings to automatic event detection due to its noisy short messages.
Finally, we discuss some future directions in this topic.
Date: Thursday, 29 May 2014
Time: 3:30pm - 5:30pm
Venue: Room 5487
Lifts 25/26
Committee Members: Dr. Lei Chen (Supervisor)
Dr. Huamin Qu (Chairperson)
Dr. Pan Hui
Dr. Raymond Wong
**** ALL are Welcome ****