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Mining Long-term Topic from a Real-time Feed

Authors:
Marijn ten Thij

Keywords: Topic Detection and Tracking; Twitter; Cluster Analysis; Content analysis; First Story Detection

Abstract:
In our current society, the availability of data has gone from scarce to abundant: huge volumes of data are generated every second. A significant part of these data are generated on social media platforms, which provide a very volatile flow of information. Leveraging the information that is buried in this fast stream of messages, poses a serious challenge. In this paper, we aim to distinguish all topics that are discussed in real-time in a social media feed by employing clustering and algorithmic techniques. We evaluate our approach by comparing the results to a post-hoc clustering approach.

Pages: 1 to 5

Copyright: Copyright (c) IARIA, 2017

Publication date: November 12, 2017

Published in: conference

ISSN: 2308-4464

ISBN: 978-1-61208-603-3

Location: Barcelona, Spain

Dates: from November 12, 2017 to November 16, 2017