During the COVID-19 pandemic, different conspiracies have risen, with the most dangerous being those focusing on vaccines. Today, there exists a social media movement focused on destroying the credibility of vaccines and trying to convince people to ignore the advice of governments and health organizations on vaccination. Our aim was to analyze a COVID-19 antivaccination message campaign on Twitter that uses Spanish as the main language, to find the key elements in their communication strategy. Twitter data were retrieved from 14 to 28 December using NodeXL software. We analyzed tweets in Spanish, focusing on influential users, most influential tweets, and content analysis of tweets. The results revealed ordinary citizens who ‘offer the truth’ as the most important profile in this network. The content analysis showed antivaccine tweets (31.05%) as the most frequent. The analysis of anti-COVID19 tweets showed that attacks against vaccine safety were the most important (79.87%) but we detected a new kind of message presenting the vaccine as a means of manipulating the human genetic code (8.1%). We concluded that the antivaccine movement and its tenets have great influence in the COVID-19 negationist movement. We observed a new topic in COVID-19 vaccine hoaxes that must be considered in our fight against misinformation.
Nowadays, a multitude of scientific publications on health science are being developed that require correct bibliographic search in order to avoid the use and inclusion of retracted literature in them. The use of these articles could directly affect the consistency of the scientific studies and could affect clinical practice. The aim of the present study was to evaluate the capacity of the main scientific literature search engines, both general (Gooogle Scholar) and scientific (PubMed, EMBASE, SCOPUS, and Web of Science), used in health sciences in order to check their ability to detect and warn users of retracted articles in the searches carried out. The sample of retracted articles was obtained from RetractionWatch. The results showed that although Google Scholar was the search engine with the highest capacity to retrieve selected articles, it was the least effective, compared with scientific search engines, at providing information on the retraction of articles. The use of different scientific search engines to retrieve as many scientific articles as possible, as well as never using only a generic search engine, is highly recommended. This will reduce the possibility of including retracted articles and will avoid affecting the reliability of the scientific studies carried out.
PubMed is a free database used daily by about 2.5 million people to search and retrieve scientific documents related to Health Sciences. In May 2020, certain changes were made to its search algorithm, which at first sight improves the location of scientific articles, but upon analyzing its operation in more depth, we detected some changes that make the reproducibility of bibliographic searches difficult. In order to safeguard the reproducibility and replicability of the searches carried out for systematic reviews, narratives and meta-analyzes, we suggest accompanying these strategies with a file in a format compatible with reference managers, to facilitate comparison and verification of the strategy to be replicated in a future.
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