Tryna b Kewl: Textual Analytics of Distorted Words among Malaysian Millennials on Twitter
Nur Nashatul Nasuha Nazman1, Kee-Man Chuah2, Su-Hie Ting3
1Nur Nashatul Nazman, Department of Language and Communication, University Malaysia Sarawak, Malaysia.
2Kee-Man Chuah, Lecturer, Department of Language and Communication, University Malaysia Sarawak, Malaysia.
3Su-Hie Ting, Associate Professor, Department of Faculty of Language and Communication, University Malaysia Sarawak, Malaysia
Manuscript received on December 15, 2019. | Revised Manuscript received on December 20, 2019. | Manuscript published on January 10, 2020. | PP: 3522-3526 | Volume-9 Issue-3, January 2020. | Retrieval Number: C7961019320/2020©BEIESP | DOI: 10.35940/ijitee.C7961.019320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The presence of Malaysian millennials on social media platforms is increasingly gaining attention particularly on Twitter. Language wise, many of them are predominantly using English and Malay in their tweets but with a touch of their own “styles” in various morphological aspects. This trend eventually leads to a rampant use of distorted vocabulary, churning out many non-standard words. This study aims to address the need in classifying the types of morphological distortions of words that are widely used among the Malaysian millennials and identify the reasons behind such trend. A total of 50 active Twitter users from Malaysia aged 18 to 30 years old were randomly chosen for this study. From each user, 20 tweets of longer than 5 words were selected for lexical analysis, giving a sum of 1000 tweets (8443 words in total). Then, interviews were conducted on 30 participants to gauge the factors of using those non-standard words. The findings revealed that the words were largely distorted in terms of its inflections so as to fit some sounds. Also, most distorted words were deliberately coined so that the millennials would appear trendy, while some were merely following the usage without knowing the actual word. This study has shown that the use of distorted words among Malaysian Twitter users did not hinder effective communication.
Keywords: Morphological Distortion, Textual Analytics, Twitter
Scope of the Article: Data Analytics