Associating Short Text Messages with Predefined Topics

Raheleh Makki
Dr. Axel Soto
Dr. Stephen Brooks
Dr. Evangelos Milios


Millions of users write about their opinions, experiences, ideas and feelings on Twitter every day. This huge amount of data contains information that is very useful for many applications. Classifying this sheer volume of tweets into different topics is a challenging task due to its short length and noisy nature. In this work, we propose a classification approach to address this challenge. We present a work in progress with preliminary experiments and a discussion on how these results can be further improved.

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