Sifting French Tweets to Investigate the Impact of Covid-19 in Triggering Intense Anxiety. Social media can be leveraged to understand public sentiment and feelings in real-time, and target public health messages based on user interests and emotions.
In this paper, we investigate the impact of the COVID-19 pandemic in triggering intense anxiety, relying on messages exchanged on Twitter. More specifically, we provide : i) a quantitative and qualitative analysis of a corpus of tweets in French related to coronavirus, and ii) a pipeline approach (a filtering mechanism followed by Neural Network methods) to satisfactory classify messages expressing intense anxiety on social media, considering the role played by emotions.
