AUTHOR=Pellert Max , Lasser Jana , Metzler Hannah , Garcia David 

TITLE=Dashboard of Sentiment in Austrian Social Media During COVID-19

JOURNAL=Frontiers in Big Data

VOLUME=3

YEAR=2020

URL=https://www.frontiersin.org/journals/big-data/articles/10.3389/fdata.2020.00032

DOI=10.3389/fdata.2020.00032

ISSN=2624-909X

ABSTRACT=<p>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 <ext-link ext-link-type="uri" xlink:href="https://apps.derstandard.at/privacywall/" xmlns:xlink="http://www.w3.org/1999/xlink">derstandard.at</ext-link>, 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 visualize that overall difference. Longitudinally, our time series showed spikes in anxiety that can be linked to several events and media reporting. Additionally, we found a marked decrease in anger. The changes lasted for remarkably long periods of time (up to 12 weeks). We have also discussed these and more patterns and connect them to the emergence of collective emotions. The interactive dashboard showcasing our data is available online at <ext-link ext-link-type="uri" xlink:href="http://www.mpellert.at/covid19_monitor_austria/" xmlns:xlink="http://www.w3.org/1999/xlink">http://www.mpellert.at/covid19_monitor_austria/</ext-link>. Our work is part of a web archive of resources on COVID-19 collected by the Austrian National Library.</p>