Using the social media platform Twitter, this study explores public reference to "scientific method(s)" in tweets specifically pertaining to COVID-19 posted between January and June 2020. The study focuses on three research questions: When did reference to scientific methods peak, which aspects of nature of science (NOS) do these tweets address, and the extent to which Twitter users' sentiments provide useful information about their attitudes towards the scientific method. COVID-19 tweets were mined and queried using "scientific method(s)" as a keyword. A content analysis using the Family Resemblance Approach (FRA) to NOS and a non-computational sentiment analysis were conducted on the obtained data set. The findings revealed that tweets using science method(s) peaked most during the months of April and May, as more information was being communicated about promising treatments and vaccine development. Most tweets were assigned multiple FRA categories. The sentiment analysis revealed that attitude towards the scientific method was predominantly supportive. Discussion of three events that were observed in clusters of tweets provided additional context. The paper concludes by noting the methodological affordances and limitations of applying the FRA for identifying NOS-related content in Twitter environments and underscoring the potential of targeted NOS messaging in promoting informed discussions about NOS in the public sphere.