Exploring the sentimental features of rumor messages and investors' intention to invest during a pandemic

Investors' decisions to invest in stock markets can be significantly influenced by online rumors generated by certain companies or influencers. The current understanding of how certain sentimental features can help increase the prediction capabilities of online rumors is still in its fancy stage. This study explored the types of topics and emotions found in rumor messages and how they are associated with investors' decisions to invest in stocks. We also investigated the potential of using these emotions in predicting investors' intention to invest in stock markets. The sentimental features consisted of users' emotions (anger, fear, sadness, joy, and trust) and polarity (positive, negative, and neutral). A topic modeling approach was applied to identify logical associations between different sentimental features of rumors on Twitter. The results showed that rumors tweets associated with investors' intention to invest were linked to the joy and trust sentiments, while the anger and fear sentiments were linked to no intention to invest. The results showed that these emotions can be used in predicting the impact of online rumors on investors' investment decisions. The prediction model can be useful for stock market prediction by enabling managers and researchers to analyze and assess the magnitudinal impact of rumors on certain investment decisions. The outcomes can also help decision and policy makers to take the required actions to prevent possible financial instability due to COVID-19 or other future events.

The Impact of Social Media Shared Health Content on Protective Behavior against COVID-19.

The use of social media has increased during the COVID-19 pandemic because people are isolated and working from home. The use of social media enhances information exchange in society and may influence public protective behavior against the COVID-19 pandemic. The purpose of this study is to identify the factors affecting public protective behavior when relying on COVID-19 pandemic-related content shared on social media. A model based on Protection Motivation Theory (PMT) was proposed and validated using a quantitative survey approach. A questionnaire was distributed to random respondents, and 488 responses were received and analyzed using Smart-PLS software. The findings showed that perceived risk, e-health literacy, public awareness, and health experts' participation influence public protective behavior when using social media to share COVID-19-relevant content. The outcomes of this study can enhance government agencies' and public health care authorities' understanding of how to use social media to raise awareness and reduce panic among the public.

Users' intention to continue using mHealth services: A DEMATEL approach during the COVID-19 pandemic.

The coronavirus disease 2019 (COVID-19) has changed the way we use and perceive online services. This study examined the influence of service quality factors during COVID-19 on individuals' intention to continue use mHealth services. A decision-making trial and evaluation laboratory (DEMATEL) approach was used to identify and analyse the relationships between service quality and individuals' intention to continue use mHealth during the COVID-19 pandemic. Individuals' direct, indirect, and interdependent behaviours in relation to service quality and continues use of mHealth were studied. A total of 126 respondents were involved in this study. The results identified several associations between service quality factors and individuals' continuous use of mHealth. The most important factor found to influence users' decision to continuously use mHealth was assurance, followed by hedonic benefits, efficiency, reliability, and content quality. The relevant cause-and-effect relationships were identified and the direction for quality improvement was discussed. The outcomes from this study can support healthcare policy makers to swiftly and widely respond to COVID-19 challenges. The findings provide fundamental insights for healthcare organisations to promote continuous use of mHealth among people by prioritising service improvements.

Telemedicine use in Sub-Saharan Africa: Barriers and policy recommendations for Covid-19 and beyond.

BACKGROUND: Telemedicine has been a useful healthcare alternative in the fight to contain the recent Covid-19 global pandemic. Yet the extent of its application and efficacy as an alternative route for healthcare provision remains a major concern for clinicians and patients. OBJECTIVE: This study sought to identify barriers to the successful implementation of telemedicine in Sub-Saharan African (SSA) countries. METHOD: A systematic review of the literature was conducted by applying the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines for identifying, selecting, evaluating and interpreting findings. RESULTS: Our results from 66 empirical studies revealed a wide usage of telemedicine technology across SSA countries but also showed insufficient evidence of usage for fighting Covid-19 infection. Further, technological, organisational, legal and regulatory, individual, financial, and cultural aspects were identified as the major barriers to the successful implementation of telemedicine in SSA. A list of recommendations was produced for each telemedicine barrier. CONCLUSION: Our review shows current trends in telemedicine application, as well as highlighting critical barriers for consideration by healthcare decision makers. This review offers a number of recommendations to support wider implementation and sustainable usage of telemedicine in SSA.