Table of Contents
Exploring boycott frames: A content analysis of Malaysian online news coverage on the 2023 McDonald’s Malaysia boycott
*Chong Hoc Wei, Wang Changsong
Abstract: This study examines how Malaysian online news organisations framed public calls to boycott McDonald’s Malaysia following heightened sensitivities surrounding the 2023 Israel–Gaza conflict. Although boycotts are widely discussed in consumer behaviour research, limited attention has been given to how news media construct boycott narratives, particularly within geopolitically charged contexts. Using inductive qualitative content analysis, the study analysed 48 news articles published between October 2023 and April 2024 across four major outlets—The Star, Berita Harian, Sin Chew Daily, and Malaysiakini. Through open coding, categorisation, and...
Abstract: This study examines how Malaysian online news organisations framed public calls to boycott McDonald’s Malaysia following heightened sensitivities surrounding the 2023 Israel–Gaza conflict. Although boycotts are widely discussed in consumer behaviour research, limited attention has been given to how news media construct boycott narratives, particularly within geopolitically charged contexts. Using inductive qualitative content analysis, the study analysed 48 news articles published between October 2023 and April 2024 across four major outlets—The Star, Berita Harian, Sin Chew Daily, and Malaysiakini. Through open coding, categorisation, and...
The impact of social media and the desire of fame towards Malaysian influencers
Nur Widad Roslan, *Muhammad Irsyad bin Zulkifli, Mohamed Hamzani bin Mohamed Izzamudin, Nur Maisarah Roslan
Abstract: This research explores the impact of social media and the pursuit of fame among Malaysian social media influencers through the lens of Uses and Gratifications Theory (UGT) and Agenda Setting Theory (AST). With the rising dominance of platforms like TikTok and Instagram, influencers have become key drivers in shaping online discourse and driving consumer behaviour. The study employed a qualitative approach by interviewing six Malaysian micro-influencers to uncover their motivations, strategies, and the emotional realities behind their public personas. Findings reveal that influencers use social media primarily for self-expression,...
Abstract: This research explores the impact of social media and the pursuit of fame among Malaysian social media influencers through the lens of Uses and Gratifications Theory (UGT) and Agenda Setting Theory (AST). With the rising dominance of platforms like TikTok and Instagram, influencers have become key drivers in shaping online discourse and driving consumer behaviour. The study employed a qualitative approach by interviewing six Malaysian micro-influencers to uncover their motivations, strategies, and the emotional realities behind their public personas. Findings reveal that influencers use social media primarily for self-expression,...
A review on multimodal approaches for deception detection: State-of-the-art, challenges, and future directions
*Md Kowsar Hossain Sakib, Neethiahnanthan Ari Ragavan, Shanjita Akter Prome,
Md Rafiqul Islam, Goh Wei Wei, David Asirvatham, Bharati Rathore
Abstract: Deception detection (DD) presents a critical challenge across high-stakes domains such as security, finance, and education, necessitating accurate, non-invasive, and portable solutions. Traditional unimodal DD systems, which often rely solely on facial expressions or basic physiological signals, exhibit inherent limitations in both accuracy and complexity. To overcome these shortcomings, multimodal approaches have become the state of the art, integrating diverse data streams, including facial cues, vocal characteristics, body language, and advanced physiological metrics, to capture deeper insights into deceptive behaviour. This literature review...
Abstract: Deception detection (DD) presents a critical challenge across high-stakes domains such as security, finance, and education, necessitating accurate, non-invasive, and portable solutions. Traditional unimodal DD systems, which often rely solely on facial expressions or basic physiological signals, exhibit inherent limitations in both accuracy and complexity. To overcome these shortcomings, multimodal approaches have become the state of the art, integrating diverse data streams, including facial cues, vocal characteristics, body language, and advanced physiological metrics, to capture deeper insights into deceptive behaviour. This literature review...
