Examining COVID-19 Tweet Diffusion Using an Integrated Social Amplification of Risk and Issue-Attention Cycle Framework.

Drawing upon the social amplification of risk (SARF) and the issue-attention cycle framework, we examined the amplification of COVID-19 risk-related tweets through (a) topics: key interests of discussion; (b) temperament: emotions of tweets; (c) topography (i.e., location); and (d) temporality (i.

COVID-19 Tweet Links: A Preliminary Investigation of Type and Relevance.

We conducted an exploratory study of the links found in Twitter tweets. Our results showed that the largest category of tweet links was social media platforms followed by alternative news sites. Government agencies and educational institutions were under-represented.

Understanding the Temporal Effects on Tweetcussion of COVID-19 Vaccine.

In the fight against COVID-19, the Pfizer and BioNTech vaccine announcement marked a significant turning point. Analysing the topics discussed surrounding the announcement is critical to shed light on how people respond to the vaccination against COVID-19. Specifically, since the COVID-19 vaccine was developed at unprecedented speed, different segments of the public with a different understanding of the issues may react and respond differently.

Understanding the effects of message cues on COVID-19 information sharing on Twitter.

Analyzing and documenting human information behaviors in the context of global public health crises such as the COVID-19 pandemic are critical to informing crisis management. Drawing on the Elaboration Likelihood Model, this study investigates how three types of peripheral cues-content richness, emotional valence, and communication topic-are associated with COVID-19 information sharing on Twitter. We used computational methods, combining Latent Dirichlet Allocation topic modeling with psycholinguistic indicators obtained from the Linguistic Inquiry and Word Count dictionary to measure these concepts and built a research model to assess their effects on information sharing.

Feasibility trial of virtual reality exposure therapy for selective mutism.

Virtual reality exposure therapy (VRET) has been commonly utilised as an extension of cognitive behavioural therapy (CBT). However, most studies examined its effectiveness among adults, with no study focusing on children with selective mutism (SM). We aimed to examine its feasibility and acceptability among children with SM.

Uncovering temporal differences in COVID-19 tweets.

In the fight against the COVID-19 pandemic, understanding how the public responds to various initiatives is an important step in assessing current and future policy implementations. In this paper, we analyzed Twitter tweets using topic modeling to uncover the issues surrounding people's discussion of the disease. Our focus was on temporal differences in topics, prior and after the declaration of COVID-19 as a pandemic.

An Interactive Mobile App Game to Address Aggression (RegnaTales): Pilot Quantitative Study.

Background: The rapid advancement in media technology has radically changed the way we learn and interact with one another. Games, with their engaging and interactive approach, hold promise in the delivery of knowledge and building of skills. This has potential in child and adolescent mental health work, where the lack of insight and motivation for therapy are major barriers to treatment.

Video Game Acceptance: A Meta-Analysis of the Extended Technology Acceptance Model.

The current study systematically reviews and summarizes the existing literature of game acceptance, identifies the core determinants, and evaluates the strength of the relationships in the extended technology acceptance model. Moreover, this study segments video games into two categories: hedonic and utilitarian and examines player acceptance of these two types separately. Through a meta-analysis of 50 articles, we find that perceived ease of use (PEOU), perceived usefulness (PU), and perceived enjoyment (PE) significantly associate with attitude and behavioral intention.

Predicting juvenile offending: a comparison of data mining methods.

In this study, the authors compared logistic regression and predictive data mining techniques such as decision trees (DTs), artificial neural networks (ANNs), and support vector machines (SVMs), and examined these methods on whether they could discriminate between adolescents who were charged or not charged for initial juvenile offending in a large Asian sample. Results were validated and tested in independent samples with logistic regression and DT, ANN, and SVM classifiers achieving accuracy rates of 95% and above. Findings from receiver operating characteristic analyses also supported these results.

Cyberbullying among adolescents: the role of affective and cognitive empathy, and gender.

The purpose of the study was to examine the association between affective empathy, cognitive empathy, and gender on cyberbullying among adolescents. Participants were 396 adolescents from Singapore with age ranging from 12 to 18 years. Adolescents responded to a survey with scales measuring both affective and cognitive empathy, and cyberbullying behavior.

Online video game therapy for mental health concerns: a review.

Background: There has been research on the use of offline video games for therapeutic purposes but online video game therapy is still fairly under-researched. Online therapeutic interventions have only recently included a gaming component. Hence, this review represents a timely first step toward taking advantage of these recent technological and cultural innovations, particularly for the treatment of special-needs groups such as the young, the elderly and people with various conditions such as ADHD, anxiety and autism spectrum disorders.

An introduction to association rule mining: an application in counseling and help-seeking behavior of adolescents.

Association rule mining (ARM) is a technique used to discover relationships among a large set of variables in a data set. It has been applied to a variety of industry settings and disciplines but has, to date, not been widely used in the social sciences, especially in education, counseling, and associated disciplines. This article thus introduces ARM and presents aspects of existing work that will be relevant and useful to researchers practitioners in the social sciences.