Abstract
In recent years, social media emerges and becomes mostly use all over the world. Social media users express their emotions by posting status with friends. Analysis of emotions of people becomes popular to apply in many application areas. So many researchers propose emotion detection systems by using Lexicon based approach. Researchers create emotion lexicons in their own languages to apply in emotional system. To detect Myanmar social media users’ emotions, lexicon does not available thus; a new word-emotion lexicon especially based on Myanmar language is needed to create. This paper describes the creation of Myanmar word-emotion lexicon, M-Lexicon that contains six basic emotions: happiness, sadness, fear, anger, surprise, and disgust. Facebook status written in Myanmar words are collected and segmented. Words in M-Lexicon is finally got by applying stop-words removal process. Finally, Matrices, Term-Frequency Inversed Document Frequency (TF-IDF), and unity-based normalization is used in lexicon creation. Experiment shows that the M-lexicon creation contains over 70% of correctly associated with six basic emotions.
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Swe, T.M., Myint, P.H. (2020). Word-Emotion Lexicon for Myanmar Language. In: Lee, R. (eds) Big Data, Cloud Computing, and Data Science Engineering. BCD 2019. Studies in Computational Intelligence, vol 844. Springer, Cham. https://doi.org/10.1007/978-3-030-24405-7_11
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DOI: https://doi.org/10.1007/978-3-030-24405-7_11
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