Tweet Classification Based on Their Lifetime Duration

by Hikaru Takemura, Keishi Tajima


Many microblog messages remain useful only within a short time, and users often find such a message after its informational value has vanished. Users also sometimes miss old but still useful messages buried among outdated ones. To solve these problems, we develop a method of classifying messages into the following three categories: (1) messages that users should read now because their value will diminish soon, (2) messages that users may read later because their value will not largely change soon, and (3) messages that are not useful anymore because their value has vanished. Our method uses an error correcting output code consisting of binary classifiers each of which determines whether a given message has value at specific time point. Our experiments on Twitter data confirmed that it outperforms naive methods.

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BibTex entry


microblog, Twitter, information filtering, information classification, real-time information, time-dependency, time-dependent data
Published in Proc. of ACM CIKM, pp.2367-2370, Oct. 2012, Maui

Copyright © 2012 by the Association for Computing Machinery, Inc. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page.
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