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Online human textual interaction often carries important emotional meanings inaccessible to computers. We propose an approach to textual emotion recognition in the context of computer-mediated communication. The proposed recognition approach works at the sentence level and uses the standard Ekman emotion classification. It is grounded in a refined keyword-spotting method that employs: a WordNet-based word lexicon, a lexicon of emoticons, common abbreviations and colloquialisms, and a set of heuristic rules. The approach is implemented through the Synesketch software system. Synesketch is published as a free, open source software library. Several Synesketch-based applications presented in the paper, such as the the emotional visual chat, stress the practical value of the approach. Finally, the evaluation of the proposed emotion recognition algorithm shows high accuracy and promising results for future research and applications.