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Sentiment Analysis of Malay Social Media Text

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Computational Science and Technology (ICCST 2017)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 488))

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Abstract

Since early 2000, sentiment analysis has grown to be one of the most active research areas in Natural Language Processing (NLP). Since then, researchers have shown a tremendous interest in building automated Sentiment analysis applications for English language and non-English languages such as Arabic Language, French language, Deutsch language, Chinese language, Italian language, etc. Yet, very limited researches have been attributed to Malay opinionated social media text despite the big number of Malay native speakers which recorded to be approximately 215 million native speaker worldwide. In this paper, a framework is proposed to tackle some of the most common challenges posed by Malay social media text (informal text). Among the features discussed in this paper are the handling of Bahasa Rojak also known as Mix language (Malay-English language), the handling of Bahasa SMS, the proper handling of Emoticon and finally the handling of Valance shifter. As a result, RojakLex lexicon was constructed consists of 4 different lexicons combined together, namely (1) MySentiDic: a Malay lexicon, (2) English Lexicon: Translated version of MySentiDic, (3) Emoticon lexicon: a combination of 9 different well known lists of commonly used online emoticons, (4) Neologism lexicon: consists of common neologism words used in Malay social media text. The proposed system shows tremendous improvement in accuracy by recording 79.28% compared to baseline which recorded 51.38% only. Discussion and implication of these findings are further elaborated.

Contact author at k.chekima@gmail.com for a copy of RojakLex.

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Authors and Affiliations

  1. Knowledge Technology Research Unit (KTRU), Faculty of Computing and Informatics, Universiti Malaysia Sabah, Jalan UMS, 88400, Kota Kinabalu, Sabah, Malaysia

    Khalifa Chekima & Rayner Alfred

Authors
  1. Khalifa Chekima
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  2. Rayner Alfred
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Corresponding authors

Correspondence to Khalifa Chekima or Rayner Alfred .

Editor information

Editors and Affiliations

  1. Knowledge Technology Research Unit, Faculty of Computing and Informatics, Universiti Malaysia Sabah, Kota Kinabalu, Malaysia

    Rayner Alfred

  2. School of Information Science, Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan

    Hiroyuki Iida

  3. Faculty of Computing and Informatics, Universiti Malaysia Sabah, Kota Kinabalu, Malaysia

    Ag. Asri Ag. Ibrahim

  4. School of Information Science, Security and Networks Area, Japan Advanced Institute of Science and Technology, Nomi, Ishikawa, Japan

    Yuto Lim

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Chekima, K., Alfred, R. (2018). Sentiment Analysis of Malay Social Media Text. In: Alfred, R., Iida, H., Ag. Ibrahim, A., Lim, Y. (eds) Computational Science and Technology. ICCST 2017. Lecture Notes in Electrical Engineering, vol 488. Springer, Singapore. https://doi.org/10.1007/978-981-10-8276-4_20

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  • DOI: https://doi.org/10.1007/978-981-10-8276-4_20

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-8275-7

  • Online ISBN: 978-981-10-8276-4

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