Dashboard of Sentiment in Austrian Social Media During COVID-19.

ABSTRACT: To track online emotional expressions on social media platforms close to real-time during the COVID-19 pandemic, we built a self-updating monitor of emotion dynamics using digital traces from three different data sources in Austria. This allows decision makers and the interested public to assess dynamics of sentiment online during the pandemic. We used web scraping and API access to retrieve data from the news platform derstandard.at, Twitter, and a chat platform for students. We documented the technical details of our workflow to provide materials for other researchers interested in building a similar tool for different contexts. Automated text analysis allowed us to highlight changes of language use during COVID-19 in comparison to a neutral baseline. We used special word clouds to visua

SUBMITTER: Pellert M 

PROVIDER: S-EPMC7931924 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature