Public Sentiment on Governmental COVID -19 Measures in D utch Social Media (2020)

Abstract: Public sentiment (the opinion, attitude or feeling that the public expresses) is a factor of interest for government, as it directly influences the implementation of policies. Given the unprecedented nature of the COVID-19 crisis, having an up-to-date representation of public sentiment on governmental measures and announcements is crucial. In this paper, we analyse Dutch public sentiment on governmental COVID-19 measures from text data collected across three online media sources (Twitter, Reddit and Nu.nl) from February to September 2020. We apply sentiment analysis methods to analyse polarity over time, as well as to identify stance towards two specific pandemic policies regarding social distancing and wearing face masks. The presented preliminary results provide valuable insights into the narratives shown in vast social media text data, which help understand the influence of COVID-19 measures on the general public.

## introduction public sentiment (the opinion, attitude or feeling that the public expresses) can directly influence the implementation of policies @xcite , therefore it is crucial for policy makers to know the public sentiment of chosen policies and to take this sentiment into account when deciding on new policies. given the unprecedented nature of the covid-19 crisis, having an up-to-date representation of public sentiment on governmental measures and announcements becomes even more important. however, the 'staying-at-home' policy makes analysing public sentiment by means of face-to-face research methods like interviews and questionnaires challenging, while classical online surveys could delay the analysis results by restrictions of frequency. with the rapid growth of online social media, monitoring public sentiment on platforms like twitter and reddit allows for much more and frequent measurements and a better indication of changes over time @xcite . thus, we apply natural language processing (nlp) approaches on dutch social media to understand the temporal variation of dutch public sentiment during the covid-19 outbreak period. our analysis covers two perspectives of sentiment analysis: polarity analysis (whether a message is positive or negative) and stance analysis (whether a message is supportive of or against a given target (li and caragea, 2019)). in our study, the given targets are policy measures taken by the dutch government. we particularly focus on the public attitude towards two specific measures, i.e., social distancing and wearing face masks. to validate our work for the broader dutch public, we collected data from three different online media platforms (twitter, reddit and nu.nl) to perform a comparison study. the preliminary results of analysis are presented in this paper. as a summary of our contributions, we provide a first sentiment-oriented overview of dutch public discussion around covid-19 across multiple social media sources and explore the practical usage of nlp approaches for understanding the influence of covid-19 measures on the general public. ## related work social media sentiment has previously been analyzed during pandemics such as h1n1 @xcite . also the covid-19 pandemic, despite being a relatively new topic, has attracted many researchers from different areas, including social media analysis. abd-alrazaq et al. (2020) identified four main covid-19 related themes on twitter: virus origin, contamination sources, preventive measures and impact on societies. zhao et al. (2020) identified topics and sentiment related to covid-19 in china. samuel et al. (2020) con-ducted textual analyses of twitter covid-19 data to identify public fear sentiment. several studies focused on bots @xcite and misinformation @xcite which influence opinions on social media. @xcite showed that positive polarity government messages on social media result in higher public engagement. @xcite identified covid-19-related topics in various social media, including reddit and twitter. they found that the ratio of misinformation to reliable information was found to be stable over time, however twitter has a larger percentage of misinformation compared to reddit. from a technical point of view, stance detection has recently received considerable attention in the nlp community @xcite , for which neural networks with word embeddings have proven to be effective @xcite ). an annotation and training approach for classifying hate speech in covid-19 related tweets using embeddings was described by @xcite . alternative approaches include unsupervised clustering for stance analysis @xcite . ## discussion and future work we present the preliminary results of sentiment analysis of dutch social media data related to the covid-19 measures across three sources. we concentrate on public polarity and stance towards two measures taken by the dutch government against the spread of the corona virus. we found that a large number of messages on dutch online media were related to the covid-19 pandemic and the polarity of those messages tended to be more negative than general messages. we assessed the stance of dutch social media messages on the national advice on social distancing and wearing face masks. the analysis showed that people widely supported social distancing when the measure was announced in march, then support declined until june and increased again recently. we think this phenomenon may be related to the the pandemic situation in the netherlands (the number of reported covid-19 patients has decreased and increased during this time as well). with respect to face masks, analysis showed that the public think face masks are useful (against the governmental measure). the rejection rates remained relatively stable over the past months. in future work we would like to improve the performance of our stance classification approach. as shown in from a practical perspective, we are interested in the explainability of our stance analysis results. we are collaborating with social scientists, who use quantitative methods (i.e. digital questionnaires and interviews) to investigate the influence of policy measures on the general public. a comparison study is planned to validate and explain the temporal trends of dutch public sentiment.