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"Beyond fear and anger: A global analysis of emotional response to Covi" by Francisco Bráulio Oliveira, Davoud Mougouei et al.

The media has been used to disseminate public information amid the Covid-19 pandemic. However, Covid-19 news has triggered emotional responses in people that have impacted their mental well-being and led to news avoidance. To understand the emotional response to Covid-19 news, we studied user comments on news published on Twitter by 37 media outlets in 11 countries from January 2020 to December 2022. We employed a deep-learning-based model to identify the basic human emotions defined by Ekman in comments related to Covid-19 news. Additionally, we implemented Latent Dirichlet Allocation (LDA) to identify the news topics. Our analysis found that while nearly half of the user comments showed no significant emotions, negative emotions were more common. Anger was the most prevalent emotion, particularly in the media and comments regarding political responses and governmental actions in the United States. On the other hand, joy was mainly linked to media outlets from the Philippines and news ....

United States , Latent Dirichlet Allocation , Fox News , Nation Africa , Covid 19 , Deep Learning , Topic Modeling ,

Information gain in SEO: What it is and why it matters

Information gain in SEO: What it is and why it matters
searchengineland.com - get the latest breaking news, showbiz & celebrity photos, sport news & rumours, viral videos and top stories from searchengineland.com Daily Mail and Mail on Sunday newspapers.

Amanda King , From Figure , Bill Slawski , Latent Dirichlet Allocation , Search Engine ,