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With the record surge of positive cases in Southeast Asia, there is a need to examine the adverse mental effects of COVID-19 among the under-researched countries. This study aims to synthesize the extant literature reporting the effects of COVID-19 pandemic on the psychological outcomes of people in Southeast Asia, and its risk factors. A scoping review was adopted targeting articles published in PubMed, Google Scholar and Scopus from January 2020 to March 30, 2021. Articles were screened using predetermined eligibility criteria, resulting in 26 papers. Elevated prevalence of adverse mental effects was noted in most of the countries as the pandemic progressed over time, with Malaysia and Philippines reporting higher prevalence rates. Mental decline was found to be more profound among the general population compared to healthcare workers and students. Dominant risk factors reported were age (younger), sex (females), education (higher), low coping skill and social/family support, and poor reliability in COVID-19 related information. Adverse mental effects were noted among population, healthcare workers and students in most of the Southeast Asian countries. Intervention and prevention efforts should be based at community-level and prioritize young adults, females, and individuals with dire financial constraints., Author(s): Vimala Balakrishnan [sup.1] , Kee Seong Ng [sup.2] , Wandeep Kaur [sup.3] , Zhen Lek Lee [sup.1] Author Affiliations: (1) grid.10347.31, 0000 0001 2308 5949, Faculty of Computer Science [...]

Introduction: Studies have indicated that users' text highlighting behaviour can be further manipulated to improve the relevance of retrieved results. This article reports on a study that examined users' text highlight frequency, length and users' copy-paste actions. Method: A binary voting mechanism was employed to determine the weights for the feedback, which were then used to re-rank the original search results. A search engine prototype was built using the Communications of the ACM test collection, with the well-known BM25 acting as the baseline model. Analysis: The proposed enhanced model's performance was evaluated using the mean average precisions and F-score metrics, and results were compared at the top 5, 10 and 15. Additionally, comparisons were also made based on the number of terms used in a query, that is single, double and triple terms. Results: The findings show that the enhanced model significantly outperformed BM25, and the rest of the models at all document levels. To be specific, the enhanced model showed significant improvements over the frequency model. Additionally, retrieval relevance was found to be the best when the query length is two. Conclusions: Users' post-click behaviour may serve as a significant indicator of their interests, and thus can be used to improve the relevance of the retrieved results. Future studies could look into further extending this model by including other post-click behaviour such as printing or saving. [Paper presented at the Information Seeking in Context (ISIC): The Information Behaviour Conference, Part 1 (11th, Zadar, Croatia, September 20-23, 2016).]

Use of mobile technology is widespread, particularly among the younger generation. There is a huge potential for utilizing such technology in lecture classes with large numbers of students, serving as an interaction tool between the students and lecturers. The challenge is to identify significant adoption factors to ensure effective adoption of mobile technology to promote interactivity between students and lecturers. This paper aims to examine factors supporting the use of mobile wireless technology during lectures to promote interactivity between students and lecturers in Malaysia's higher education institutions. A survey involving higher education students enrolled in on-campus academic courses in Malaysia was conducted with a sample size of 302. Factor analysis results identified five factors: independent variables System Usefulness (SU), User System Perception (USP), User Uncertainty Avoidance (UUA), System and Information Quality (SIQ), and dependent variable Mobile Wireless Technology Adoption for Interactive Lectures (MWT-AIL). All independent variables are positively associated to MWT-AIL, with UUA and SIQ having higher levels of significance compared to SU and USP. Respondents were selected from higher learning institutions from urban areas in Malaysia. Therefore results obtained are not representative of the entire higher education landscape in Malaysia, and future studies are warranted to include higher learning institutions located in rural areas. It is hoped that findings from this study will serve as a catalyst for future studies to be conducted, particularly among higher education researchers seeking ways to utilize technology effectively to enhance the learning experiences of students.

This study investigates the socio-demographic predictors for misinformation sharing and authenticating behavior among Malaysian young adults, based on data collected during the COVID-19 pandemic through a self-reporting survey. A total of 833 Malaysians aged between 18 and 35 years old were recruited. Results indicate that 64.5% (n = 537) of the respondents authenticated suspicious news, 16% (n = 133) shared misinformation knowingly, while 30% (n = 250) did so unknowingly. Frequency of sharing news (β = 0.229, p < 0.001), frequency of social media use (β = 0.135, p = 0.03), frequency of access to online news portals (β = - 0.141, p = 0.007) and the ability to identify misinformation (β = -0.161, p < 0.001) significantly predicted misinformation sharing. Conversely, only frequency of sharing news (β = -0.425; p < 0.001) and importance of reading real news (β = 0.873; p < 0.001) predicted authentication behavior. Findings suggest that the majority of the misinformation sharing behavior is accidental instead of intentional, and proposes several strategies that can be adopted to mitigate the wide spread of misinformation including seminars and trainings to improve an individual's social media literacy, critical thinking and analytical skill and also one's social responsibility as a good citizen. [ABSTRACT FROM AUTHOR]

The present study aims to improve sarcasm detection mechanisms using multiple hyperboles such as interjection, intensifiers, capital letters, punctuation, and elongated words. A non-bias dataset consisting of the current pandemic related hashtags was used, namely #Chinesevirus and #Kungflu. Analysis and evaluation were performed with three distinguished machine learning algorithm that is Support Vector Machine, Random Forest and Random Forest with bagging classifiers. Each feature were analysed and the most significant hyperbole identifying sarcasm was assessed further by combining with other hyperboles. The experiments and analysis conducted using these hyperboles concluded that as a single or combined features, hyperboles enhance sarcasm especially in an unbiased dataset. [ABSTRACT FROM AUTHOR]

The current study sets out to identify determinants affecting tertiary students' behavioural intentions to use mobile technology in lectures. The study emphasises that the reason for using mobile technology in classrooms with large numbers of students is to facilitate interactions among students and lecturers. The proposed conceptual framework has four main antecedents of behavioural intention: system perception, intrinsic motivation, system and information quality, and uncertainty avoidance. Sample data was collected from 396 tertiary students in Malaysia. Results from structural equation modelling on the sample indicated that behavioural intention was significantly influenced by system and information quality, followed by intrinsic motivation, and uncertainty avoidance. System perception was not significantly predictive of behavioural intention. The proposed framework explained 54% of the variance in behavioural intention of mobile technology use in lecture classes. The study findings are indicative of the importance of system development efforts to ensure overall quality system design. The findings further suggest that mobile technology may serve as a tool to facilitate interaction among students and lecturers in large lecture classes.

This study is an investigation into factors that encourage and/or inhibit the use of social media in the academic learning process between Australian and Malaysian students at higher learning institutions. Push-pull-mooring theory was used as a guide, resulting in seven independent variables ("convenience", "social influence", "academic reasons", "ease of use", "social networking", "barriers", and "e-learning perception"), and one dependent variable (teaching and learning benefit). The study included a survey of 524 respondents (N[subscript Australia] = 214; N[subscript Malaysia] = 310). Path modeling analysis revealed three common factors between students from both countries: academic reasons, barriers, and social networking. However Malaysian students revealed a significant greater emphasis on academic reasons and barriers compared to their Australian counterparts. No significant difference was noted for social networking, suggesting that the use of social media as a means to maintain social interaction is popular regardless of cultural differences. Alternatively, significant effects were observed for convenience and e-learning perception among Australian students, while ease of use was found to have significant impact on Malaysian students. The findings suggest that cultural differences and the education system will impact the use of social media as an online learning tool.

This paper investigates the effect of users' personality traits and emotions expressed through textual communications on YouTube to detect cyberbullying using a series of ensemble classifiers. Personality traits were determined using the Big Five model whereas emotions were based on Ekman's basic emotion theory. Annotated YouTube textual comments in English (N = 5152; i.e. 2576 number of bullying versus 2576 non-bullying instances) were used to detect cyberbullying incidents using several ensemble classifiers, including Random Forest and AdaBoost. Performance metrics revealed both personality traits and emotion to significantly improve the identification of cyberbullying presence, with accuracy and F-score values of more than 95%. Further fine-grained analysis revealed anger and openness to be more profound compared to other emotions and personalities. Further, neurotic individuals tend to be driven to cyberbullying by joy, disgust and fear. The findings show that personality and emotions play pertinent roles in cyberbullying, and the identification of specific traits and emotions can help in designing a more strategic intervention programme. [ABSTRACT FROM AUTHOR]