EMOTION RECOGNITION IN POLISH TEXTS BASED ON KEYWORDS DETECTION METHOD
Dynamic development of social networks caused that the Internet has become the most popular communication medium. A vast majority of the messages are exchanged in text format and very often reflect authors’ emotional states. Detection of the emotions in text is widely used in e-commerce or telemedicine becoming the milestone in the field of human-computer interaction. The paper presents a method of emotion recognition in Polish-language texts based on the keywords detection algorithm with lemmatization. The obtained accuracy is about 60%. The first Polish-language database of keywords expressing emotions has been also developed.
emotion recognition; human computer interaction; natural language processing; text processing
Binali H., Wu C., Potdar V.: Computational approaches for emotion detection in text, 4th IEEE International Conference on Digital Ecosystems and Technologies, Dubai, 2010, 172–177 [DOI:10.1109/DEST.2010.5610650].
Buckland M., Gey F.: The Relationship between Recall and Precision. Journal of The American Society For Information Science 45(1)/1994, 12–19 [DOI:10.1002/(SICI)1097-4571(199401)45:1<12::AID–ASI2>3.0.CO;2-L].
Dung T., Cao T.H.: A high-order hidden Markov model for emotion detection from textual data. Lecture Notes in Computer Science 7457/2012, 94–105.
Ekman P.: Basic emotions. The handbook of cognition and emotion. John Wiley & Sons, New York 1999.
Elliott C.: The affective reasoned: a process model of emotions in a multi-agent system. Doctoral thesis on Northwestern University, 1992.
Fellbaum C.: WordNet: An Electronic Lexical Database. MIT Press, Cambridge 1998.
Ghazi D., Inkpen D., Szpakowicz S.: Hierarchical versus flat classification of emotions in text. NAACL HLT 2010 workshop on computational approaches to analysis and generation of emotion Computational Linguistics, 2010, 40–146.
Hancock J., Landrigan C., Silver C.: Expressing emotion in text-based communication. Proceedings of the SIGCHI conference on Human factors in computing systems, 2007, 929–932.
Kamińska D., Pelikant A.: Recognition of Human Emotion from a Speech Signal Based on Plutchik’s Model. International Journal of Electronics and Telecommunications 58(2)/(2012), 165–170[DOI:10.2478/v10177-012-0024-4].
Khalili Z., Moradi M.H.: Emotion recognition system using brain and peripheral signals: using correlation dimension to improve the results of EEG. Proceedings of the International Joint Conference on Neural Networks 2009, 1571–1575.
Ling H., Bali R., Salam R.: Emotion detection using keywords spotting and semantic network. Proceedings of the International Conference on Computing & Informatics 2006, 1-5 [DOI:10.1109/ICOCI.2006.5276495].
Lu Ch., Lin S., Liu J., Cruz-Lara S., Hong J.: Automatic event-level textual emotion sensing using mutual action histogram between entities. Expert systems with applications 37(2)/2010, 1643–1653[DOI:10.1016/j.eswa.2009.06.099].
Maziarz M., Piasecki M., Szpakowicz S.: Approaching plWordNet 2.0. Proceedings of the 6th Global Wordnet Conference, 2012.
Plutchik R.: The nature of emotion. American Scientist 89(4)/2001, 344.
Schachter S., Singer J.: Cognitive, Social, and Physiological Determinants of Emotional State. Psychological Review 69/1962, 379–399 [DOI:10.1037/h0046234].
Stathopoulou I-O., Tsihrintzis G.: Emotion Recognition from Body Movements and Gesture. Proceedings of the International Conference on Intelligent Interactive Multimedia Systems and Services, 2011, 295–303.
Strapparava C., Valitutti A.: WordNet Affect: an Affective Extension of WordNet. Proceedings of International Conference on Language Resources and Evaluation, 2004, 1083–1086.
Ślot K., Bronakowski Ł., Cichosz J.: Application of voiced-speech variability descriptors to emotion recognition. Computational Intelligence for Security and Defense Applications, 2009, 1–5 [DOI:10.1109/CISDA.2009.5356537].
Teng Z., Ren F., Kuroiwa S.: Recognition of Emotion with SVM. Artificial Intelligence 4114/2006, 701–710 [DOI:10.1007/11816171_87].
Zheng W., Tang H., Lin Z., Huang T.: Emotion Recognition from Arbitrary View Facial Images. Proceedings of the 11th European Conference on Computer Vision, 2010, 490–503 [DOI:10.1007/978-3-642-15567-3_36].
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