We use numbers of Covid-related tweets over Dutch regions in month 1-9 of 2020. Peaks in tweets precede the peaks of infections by about one month (the exception is June when the corona emergency law (“Spoedwet”) was introduced, which drew a lot of online comments. The reason for this time lag is that more positive sentiments, which resulted in fewer tweets, occurred during peak infections. Just before, more negative sentiments dominated causing more tweets. This positivity in tweets during peak infections has, no doubt, various reasons. Yet, one reason may be in how people value society: the higher the number of infections, the more positive the sentiments related to crucial occupations became, which resulted in fewer tweets. This relation does not hold for non-crucial occupations.
|Place of Publication||Munich|
|Publisher||Munich Personal RePEc Archive|
|Number of pages||11|
|Volume||MPRA Paper No. 110879|
|Publication status||Published - 2021|
- Sentiment analysis