A taxonomy of Malay social media text

Abstract

<span>In this paper, we proposed a preliminary taxonomy of Malay social media text. Performing text analytics on Malay social media text is a challenge. The formal Malay language follows specific spelling and sentence construction rules. However, the Malay language used in social media differs in both aspects. This impedes the accuracy of text analytics. Due to the complexity of Malay social media text, many researches has chosen to focus on classifying the formal Malay language. To the best of our knowledge, we are the first to propose a formal taxonomy for Malay text in social media. Narrow and informal</span><span lang="EN-GB"> categorisations</span><span> of Malay social media text can be found amidst efforts to pre-process social media text, yet cherry-picked only some categories to be handled. We have differentiated Malay social media text from the formal Malay language by identifying them as Social Media Malay Language or SMML. They consists of </span><em><span lang="EN-GB">spelling variations</span></em><span lang="EN-GB">, <em>Malay-English mix sentence</em>, <em>Malay-spelling English words</em>, <em>slang-based words,</em> <em>vowel-les words, number suffixes </em>and<em> manner of expression.</em></span><span>This taxonomy is expected to serve as a guideline in research and commercial products.</span>

Detecting candidates of depression, anxiety and stress through malay-written tweets: a preliminary study

“…More so in a language like Malay which has been identified as restricted in resources [17]. Differing from the formal Malay language in terms of spelling and sentence construction, Malay social media text has been identified to have spelling variations, sentences with a mix of English and Malay, English words spelt using Malay convention, words based on regional Malaysian slang, words without vowels and words to indicate emphasis [17]. This work aims at detecting candidates of depression, anxiety and stress through Malay-written tweets based on the M-DASS-42 framework.…”