Dataset Open Access
Social behavior has a fundamental impact on the dynamics of infectious diseases (such as COVID-19), challenging public health mitigation strategies and possibly the political consensus. The widespread use of the traditional and social media on the Internet provides us with an invaluable source of information on societal dynamics during pandemics. With this dataset, we aim to understand mechanisms of COVID-19 epidemic-related social behavior in Poland deploying methods of computational social science and digital epidemiology. We have collected and analyzed COVID-19 perception on the Polish language Internet during 15.01-31.07(06.08) and labeled data quantitatively (Twitter, Youtube, Articles) and qualitatively (Facebook, Articles and Comments of Article) in the Internet by infomediological approach.
- manually labelled1,449 articles / Facebook posts from Lower Silesia (facebook_articles_lower_silesia.zip) and 111 texts from outside this region;
-manually labelled 1000 most popular tweets (twits_annotated.xlsx) with cathegories is_fake (categorical and numeric) topic and sentiment;
-extracted 57,306 representative articles (articles_till_06_08.zip) in Polish using Eventregitry.org tool in language Polish and topic "Coronavirus" in article body;
- extracted 1,015,199 (tweets_till_31_07_users.zip and tweets_till_31_07_text.zip) and Tweets from #Koronawirus in language Polish using Twitter API.
- collected 1,574 videos (youtube_comments_till_31_07.zip and youtube_movie.csv) with keyword: Koronawirus on YouTube and 247,575 comments on them using Google API;
- We supplemented the media observations with an analysis of 244 social empirical studies till 25.05 on COVID-19 in Poland (empirical_social_studies.csv).
Reports and analyzes and coding books can be found in Polish at: http://www.infodemia-koronawirusa.pl
Jarynowski A, Wójta-Kempa M, Belik V. TRENDS IN PERCEPTION OF COVID-19 IN POLISH INTERNET, Polish Epidemiological Review
Jarynowski A, Wójta-Kempa M, Płatek D, Krzowski Ł, Belik V. Spatial Diversity of COVID-19 Cases in Poland Explained by Mobility Patterns - Preliminary Results 2020; http://dx.doi.org/10.2139/ssrn.3621152