This work aims at constructing a Malay language psychometric dictionary from Facebook statuses for LIWC by using the direct translation approach. The linguistic were obtained from 160 Malaysian Facebook users with an extracted textual data derived from 12573 wall-posted statuses. The
jury method is used to assign each word to its correct category by comparing the direct translation of the word in Malay versus the English word in the English psychometric dictionary. LIWC classifies words by categories thus assigning the correct ones to the most precise translations and
usage are essential. The work successfully categorized 2820 Malay words from the Malaysian Facebook statuses. This methodological note declares the creation of the Malay language version of the LIWC and the exemplary application of the dictionary in classifying personality of extraversion
of the Malaysian Facebook users. The constructed Malay LIWC dictionary can be applied to any natural language processing framework or machine learning area that focuses on mining the Malay text language.
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Natural Language Processing;
Document Type: Research Article
Faculty of Computer Science and Mathematics, Universiti Teknologi MARA (UiTM) Melaka Kampus Jasin, 77300 Merlimau, Melaka, Malaysia
School of Computer Sciences, Universiti Sains Malaysia, 11800 Minden, Penang, Malaysia
Publication date: 01 August 2017
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