ArticleHeliyon2021
Digital citizens' feelings in national #Covid 19 campaigns in Spain.
Article in Heliyon, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Understanding COVID: Collaborative Government Campaign for Citizen Digital Health Literacy in the COVID-19 Pandemic.Life (Basel, Switzerland) · 2023Article
- Article
- Public sentiment analysis and topic modeling regarding COVID-19 vaccines on the Reddit social media platform: A call to action for strengthening vaccine confidence.Journal of infection and public health · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn 2020 Spain launched an official campaign, #EsteVirusLoParamosUnidos, aimed at uniting the entire country through citizen cooperation, in order to combat Covid-19. The objective of this research has been to analyse how this Twitter campaign revealed the feelings expressed by Spanish citizens.
methodsThe research is based on a composite design that triangulates, from a theoretical model, a quantitative analysis and a qualitative analysis.
resultsOf the 7,357 tweets in the sample, 72.32% were found to be retweets. Four content families were extracted which relate to politics, education, messages to society and the defence of occupational groups. The feelings expressed ranged from those of unity, admiration and support to those of discontent and criticism of issues regarding the health situation.
conclusionsThe development of networked socio-political and technical measures, which enabled citizen participation, facilitated the development of new patterns of interaction between national or regional governments and digital citizens. This increased citizens' possibilities of influencing the public agenda and, therefore, strengthening citizen engagement regarding specific situations.
Indexed as
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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.