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In this paper we propose to approach the subject of Twitter Topic Detection using a new technique called Topic Fuzzy Fingerprints. A comparison is made with two popular text classification techniques, Support Vector Machines (SVM) and k-Nearest Neighbours (kNN). Preliminary results show that Twitter Topic Fuzzy Fingerprints outperforms the other two techniques achieving better Precision and Recall, while still being much faster, which is an essential feature when processing large volumes of streaming data.doi:10.1109/fuzz-ieee.2014.6891781 dblp:conf/fuzzIEEE/RosaBC14 fatcat:g545gv4mxzacdpebmub2qaniem