Exploring TikTok user-generated content for business intelligence using enhanced data, information, knowledge and wisdom (DIKW) framework

Ahmad Asmawi, Muhammad Akmal Hakim (2026) Exploring TikTok user-generated content for business intelligence using enhanced data, information, knowledge and wisdom (DIKW) framework. Masters thesis, Universiti Teknologi MARA (UiTM).

Abstract

This research aims to develop a systematic pipeline for transforming TikTok User-Generated Content (UGC) into actionable Business Intelligence (BI) for brands within Malaysia’s beauty and personal care sector. While TikTok has become a primary hub for consumer expression, its unstructured and linguistically complex comments characterized by Malaysian slang and code-switching hinder the extraction of reliable insights. To address this, the study adopts the Data-Information-Knowledge-Wisdom (DIKW) hierarchy and the Data Science Trajectories (DST) methodology as its core frameworks.

Metadata

Item Type:	Thesis (Masters)
Creators:	Creators Email / ID Num. Ahmad Asmawi, Muhammad Akmal Hakim 2024655976
Contributors:	Contribution Name Email / ID Num. Thesis advisor Isawasan, Pradeep UNSPECIFIED
Subjects:	H Social Sciences > HM Sociology > Social psychology > Social influence. Social pressure H Social Sciences > HM Sociology > Groups and organizations > Social groups. Group dynamics > Social networks
Divisions:	Universiti Teknologi MARA, Shah Alam > Faculty of Computer and Mathematical Sciences
Programme:	Master of Science (Information Technology)
Keywords:	Bibliometric analysis, Social media, User generated content
Date:	2026
URI:	https://ir.uitm.edu.my/id/eprint/134414