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buried among outdated ones.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.
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