University of Illinois Urbana-Champaign

A preliminary approach to detect and track events in social media

Tang, Minyi

Content Files
TANG-THESIS-2016.pdf

Permalink

https://hdl.handle.net/2142/90843

Description

Title
A preliminary approach to detect and track events in social media
Author(s)
Tang, Minyi
Issue Date
2016-04-28
Director of Research (if dissertation) or Advisor (if thesis)
Abdelzaher, Tarek F.
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Date of Ingest
2016-07-07T20:35:24Z
Keyword(s)
  • Social Event Tracking
  • Data Mining
Abstract
Many algorithms have been proposed to model spatiotemporal events in both sensor network and social networks. However, most of them can not fullfil the task in a social network data streaming context. We proposed an evolving Mean Shift clustering based algorithm to formulate a robust system to automatically detect and track events in social network media. We also demonstrate its performance in empirical experiments. Our online system can be udapted and maintained without comsuming too much system resources which may formulate a good basis for event detection and tracking in the domain of real-time social network media.
Graduation Semester
2016-05
Type of Resource
text
Permalink
http://hdl.handle.net/2142/90843
Copyright and License Information
Copyright 2016 Minyi Tang

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Graduate Dissertations and Theses at Illinois PRIMARY
Graduate Theses and Dissertations at Illinois