ArticleData in brief2020
A first public dataset from Brazilian twitter and news on COVID-19 in Portuguese.
Article in Data in brief, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- An augmented multilingual Twitter dataset for studying the COVID-19 infodemic.Social network analysis and mining · 2021Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this data article, we provide a collection of 3,925,366 tweets and 18,413 online news around the online discussion about COVID-19 in Brazil. The data from Twitter were collected through Twitterscraper Python library and we considered a set of keywords in Portuguese regarding to COVID-19. In order to facilitate the identification of tweets that have hashtags, media and retweets for researchers or data enthusiasts, we created three specific datasets for each of these categories. The news on COVID-19 was collected from the UOL portal, the most popular Brazilian website. All the data were gathered from January to May, 2020. These datasets can attract the attention from communities such as data science, social science, natural language processing, tourism, infodemiology, and public health.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.