LEKSIKON UNTUK DETEKSI EMOSI DARI TEKS BAHASA INDONESIA

Julius Bata, Suyoto Suyoto, Pranowo Pranowo

Abstract


Deteksi emosi dari teks merupakan bidang penelitian yang menarik perhatian beberapa tahun terakhir. Salah satu komponen utama dalam deteksi emosi adalah leksikon emosi. Makalah ini memaparkan proses pengembangan leksikon emosi untuk bahasa Indonesia. Pengembangan leksikon terdiri dari 2 proses utama yaitu pemilihan seed words dan perluasan leksikon. Pemilihan seed words dilakukan berdasarkan jenis emosi yaitu senang, cinta, marah, takut dan sedih. Jumlah seed words yang digunakan sebanyak 124 kata. Perluasan leksikon dilakukan menggunakan Tesaurus Bahasa Indonesia. Setiap kata dalam leksikon diberi bobot biner 1 atau 0. Leksikon emosi yang dihasilkan terdiri dari 1165 kata.

References


Aman, S. & Szpakowicz, S., 2007. Identifying Expressions of Emotion in Text. In Text, Speech and Dialogue, Lencture Notes in Artificial Intelligence Vol 4629, pp. 196-205.

Anusha, V. & Sandhya, B., 2015. A Learning Based Emotion Classifier With Semantic Text Processing. Advances in Intelligent Systems and Computing Vol 320, pp. 371-382.

Bandhakavi, A., Wiratunga, N., Deepak, P., & Massie, S., 2014. Generating a Word-Emotion Lexicon from #Emotional Tweets. Proc of the Third Joint Conference on Lexical and Computational Semantics (*SEM 2014), pp. 12-21.

Binali, H., & Potdar, V., 2012. Emotion Detection State of the Art. Proc of the CUBE International Information Technology Conference on CUBE 2012, ACM Press, pp. 501-507.

Calvo, R. A., & D’Mello, S., 2010. Affect Detection: An Interdisciplinary Review of Models, Methods, and Their Applications. IEEE Transactions on Affective Computing 1(1), pp. 18-37.

Calvo, R. A., & Kim, M. K., 2013. Emotions In Text: Dimensional And Categorical Models. Computational Intelligence 29(3), pp. 527-543.

Chaumartin, F.R., 2007. UPAR7: A knowledge-based system for headline sentiment tagging. Proc of the Fourth International Workshop on Semantic Evaluations (SemEval-2007), pp. 422–425.

Ghazi, D., Inkpen, D. & Szpakowicz, S., 2010. Hierarchical approach to emotion recognition and classification in texts. Advances in Artificial Intelligence LNCS Vol 6085, pp. 40-50.

Ghazi, D., Inkpen, D. & Szpakowicz, S., 2014. Prior and contextual emotion of words in sentential context. Computer Speech and Language 28, pp. 76-92.

Gupta, N., Gilbert, M., & Di Fabbrizio, G., 2013. Emotion Detection in Mail Customer Care. Computational Intelligence 29(3), pp. 489-505.

Hancock, J.T., Landrigan, C., & Silver, C., 2007. Expressing emotion in text-based communication. Proc of the SIGCHI Conference on Human Factors in Computing Systems, ACM, pp. 929–932.

Hirat, R., & Mittal, N., 2015. A Survey On Emotion Detection Techniques using Text in Blogposts. International Bulletin of Mathematical Research Vol 2, Issue 1, pp. 180-187.

Krcadinac, U., Pasquier, P., Jovanovic, J. & Devedzic, V., 2013. Synesketch: An Open Source Library for Sentence-Based Emotion Recogntion. IEEE Transactions on Affective Computing 4(3), pp. 312-325.

Li, J., & Ren, F., 2011. Creating a Chinese Emotion Lexicon Based on Corpus Ren-CECps. Proc of IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS), pp. 80-84.

Li, W., & Xu, H., 2014. Text-based emotion classification using emotion cause extraction. Expert System with Applications 41, pp. 1742-1749.

Lopatovska, I., & Arapakis, I., 2010. Theories, methods and current research on emotions in library and information science, information retrieval and human-computer interaction. Information Processing and Management 47(4), pp. 575-592.

Mohammad, S.M., 2012a. From once upon a time to happily even after: Tracking emotions in mail and books. Decision Support Systems 53, pp. 730-741.

Mohammad, S.M., 2012b. Portable features for classifying emotional text. Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 587-591.

Mohammad, S.M., 2012c. #Emotional Tweets. Proc of First Joint Conference on Lexical and Computational Semantics (*SEM), pp. 246-255.

Mohammad, S.M., & Turney, P.D., 2013. Crowdsourcing a word-emotion association lexicon. Computational Intelligence 29(3), pp. 436-465.

Mohammad, S.M., & Kiritchenko, S., 2015. Using Hashtags to Capture Fine Emotion Categories from Tweets. Computational Intelligence 31(2), pp. 301-326.

Neviarouskaya, A., Prendinger, H., & Ishizuka, M., 2011. Affect Analysis Model: novel rule-based approach to affect sensing from text. Natural Language Engineering 17, pp. 95-135.

Poria, S., Gelbukh, A., Das, D., & Bandyopadhyay, S., 2013. Fuzzy Clustering for Semi-supervised Learning – Case Study: Construction of an Emotion Lexicon. I. Batyrshin and M. González Mendoza (Eds.): MICAI 2012, Part I, LNAI 7629, pp. 73–86.

Quan, C., & Ren, F., 2013. Finding Emotional Focus for Emotion Recognition at Sentence Level. Chinese Journal of Electronics 22(1), pp. 99-103.

Shaver, P.R., Murdaya, U., & Fraley, R.C., 2001. Structure of the Indonesian emotion lexicon. Asian Journal of Social Psychology Vol 4, pp. 201-224.

Staiano, J., & Guerini, M., 2014. DepecheMood: a Lexicon for Emotion Analysis from Crowd-Annotated News. Proc of the 52nd Annual Meeting of the Association for Computational Linguistics, pp. 427-433.

Strapparava, C., & Valitutti, A., 2004. WordNetAffect: an affective extension of WordNet. Proc of the Conference on International Language Resources and Evaluation (LREC), pp. 1083-1086.

Strapparava, C., & Mihalcea, R., 2008. Learning to identify emotions in text. SAC’08: Proc of the 2008 ACM symposium on Applied computing, pp. 1556-1560.

Tao, J., & Tan, T., 2005. Affective Computing: A Review. J. Tao, T. Tan, and R.W. Picard (Eds.): ACII 2005, LNCS 3784, pp. 981-995.

Vania, C., Ibrahim, M., & Adriani, M., 2014. Sentiment Lexicon Generation for an Under-Resourced Language. International Journal of Computational Linguistic and Applications 5(1), pp. 59-72.

Wicaksono, A. F., Vania, C., Distiawan, T. B. & Adriani, M., 2014. Automatically Building a Corpus for Sentiment Analysis on Indonesian Tweets. Proc of the 28th Pacific Asia Conference on Language, Information and Computation, pp. 185-194

Xu, G., Meng, X., & Wang, H., 2011. Build Chinese Emotion Lexicons Using A Graph-based Algorithm and Multiple Resources. Proc of the 23rd International Conference on Computational Linguistics (Coling 2010), pp. 1209-1217.

Yang, C., Lin, K.H-Y., & Chen, H-H., 2007. Building Emotion Lexicon from Weblog Corpora. Proc of the ACL 2007 Demo and Poster Sessions, pp. 133-136.


Refbacks

  • There are currently no refbacks.
slot gacor slot gacor hari ini slot gacor 2025 demo slot pg slot gacor slot gacor