ArticleCurrent research in parasitology & vector-borne diseases2021
Recent trends in the use of social media in parasitology and the application of alternative metrics.
Article in Current research in parasitology & vector-borne diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
5 citing papers in PubMed.
- Explosion of research on psychopathology and social media use after COVID-19: A scientometric study.World journal of psychiatry · 2024Article
- Which Topics Drive Dissemination? Alternative Bibliometrics Analysis of the Highest-Ranking Articles in 3 Infectious Diseases Journals Before COVID-19.Open forum infectious diseases · 2024Article
- Social media as a tool for detecting underdiagnosed parasitic infections: the case of spirocercosis.Parasitology research · 2023Article
- Twitter trends in #Parasitology determined by text mining and topic modelling.Current research in parasitology & vector-borne diseases · 2023Article
- 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
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent times, the use of social media for the dissemination of "news and views" in parasitology has increased in popularity. News, Twitter and Blogs have emerged as commonplace vehicles in the knowledge dissemination and transfer process. Alternative metrics ("altmetrics"), based on social media mentions have been proposed as a measure of societal impact, although firm evidence for this relationship is yet to be found. Nevertheless, increasing amounts of data on "altmetrics" are being analysed to identify the nature of the unknown impact that social media is generating. Here, we examine the recent, and increasing use of social media in the field of parasitology and the relationship of "altmetrics" with more traditional bibliometric indicators, such as article citations and journal metrics. The analyses document the rise and dominance of Twitter as the main form of social media occurring in the discipline of parasitology and note the contribution to this trend of Twitter bots that automatically tweet about publications. We also report on the use of the social referencing platform Mendeley and its correlation to article citations; Mendeley reader numbers are now considered to provide firm evidence on the early impact of research. Finally, we consider the Twitter profile of 31 journals publishing parasitology research articles (by volume of papers published); we show that 13 journals are associated with prolific Twitter activity about parasitology. We hope this study will stimulate not only the continued and responsible use of social media to disseminate knowledge about parasitology for the greater good, but also encourage others to further investigate the impact and benefits that altmetrics may bring to this discipline.
Indexed as
Identifiers
What OpenQuestion holds
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.