Abstract
Word emotion analysis is the basic step that recognizes emotions. Emotion words that express emotion on dialogs are classified into two classes such as direct and potential emotion word. Direct emotion word can represent clearly emotion and potential emotion word may represent specific emotion depending on context. Potential emotion word unlike direct emotion word is hardly extracted and identified. In this paper, we propose the method that extracts and identifies potential emotion words based on WordNet as well as direct emotion words. Potential emotion word can be extracted by measuring lexical affinity. Then, we consider the sense distance in order to minimize variation of meaning. In addition, we suggest the maximum sense distance that limits searching space and can extract the best potential emotion words.
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References
Binali H, Wu C, Potdar V (2010) Computational approaches for emotion detection in text. Digital ecosystems and technologies (DEST), 4th IEEE international conference on, pp 172–177
Quan C, Ren F (2010) Automatic annotation of word emotion in sentences based on Ren-CECps. In: Proceedings of the seventh conference on international language resources and evaluation (LREC’10), pp 1146–1151
Chen L, Chen G-C, Xu C-Z, March J, Benford S (2008) Emoplayer: a media player for video clips with affective annotations. Interact Comput 20:17–28
Salway A, Graham M (2003) Extracting information about emotions in films. In: Proceedings of the eleventh ACM international conference on multimedia (MULTIMEDIA ‘03), pp 299–302
Yassine M, Hajj H (2010) A framework for emotion mining from text in online social networks. IEEE international conference on data mining workshops (ICDMW), pp 1136–1142
Liu H, Lieberman H, Selker T (2003) A model of textual affect sensing using real-world knowledge. In: Proceedings of the 2003 international conference on intelligent user interfaces, pp 125–132
Ortony A, Clore GL, Collins A (1988) The cognitive structure of emotions. Cambridge University Press, Cambridge
Richardson R, Smeaton AF, Murphy J (1994) Using wordnet as a knowledge base for measuring semantic similarity between words. Working paper CA-1294, Dublin city university, school of computer application, Dublin, Ireland. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.49.6027&rep=rep1&type=ps
Willegen IV, Rothkrantz LJM, Wiggers P (2009) Lexical affinity measure between words. In: Proceedings of TSD, pp 234–241
Strapparava C, Valitutti A (2004) WordNet-affect: an affective extension of WordNet. In: Proceedings of the 4th international conference on language resources and evaluation, pp 1083–1086
Esuli A, Sebastiani F (2006) SENTIWORDNET: a publicly available lexical resource for opinion mining. In: Proceedings of the 5th conference on language resources and evaluation (LREC’06), pp 417–422
Elliot C (1992) The affective reasoner: a process model of emotions in a multi-agent system. PhD thesis, Northwestern University, The institute for the learning sciences, Technical report no. 32
Ma C, Prendinger H, Ishizuka M (2005) Emotion estimation and reasoning based on affective textual interaction. In: Proceedings of affective computing and intelligent interaction, first international conference (ACII 2005), pp 622–628
Park S-B, Yoo E, Kim H, Jo G-S (2010) Automatic emotion annotation of movie dialogue using WordNet. In: Proceedings of the third international conference on intelligent information and database systems, vol Part II, pp 130–139
Danisman T, Alpkocak A (2008) Feeler: emotion classification of text using vector space model. In: AISB 2008 convention, communication, interaction and social intelligence 2:53–59
Acknowledgements
This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MEST) (No. 2011-0017156).
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Park, SB., You, E., Jung, J.J. (2012). Potential Emotion Word in Movie Dialog. In: Kim, K., Ahn, S. (eds) Proceedings of the International Conference on IT Convergence and Security 2011. Lecture Notes in Electrical Engineering, vol 120. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-2911-7_48
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DOI: https://doi.org/10.1007/978-94-007-2911-7_48
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