As the COVID-19 virus became a pandemic in March 2020, the amount of (time-stamped written) data, such as news/newspaper reports, scientific articles, social media posts (e.g. blogs and twitter), surveys and other information about the virus and its symptoms, prevention, management and transmission became massively available. Such data contained both valid and reliable information, and relevant facts from trusted sources and also rumors, conspiracy theories and misinformation from unofficial ones.
Blog posts
A Swedish COVID-19 (sv-COVID-19) corpus and its exploration ... smorgasbord
The Gothenburg H70 birth cohort studies and the digital assessment of neuropsychological tests
A comment often received by the reviewers of manuscripts to scientific conferences and journals is one about the representative sample under scrutiny and whether there are any solid arguments for accepting that the population characteristics, and particularly the features extracted from the empirical data acquired from such a population (e.g. from speech production) provide sufficient or accurate enough information to use in various algorithmic approaches (e.g. in machine learning).