ArticleJournal of healthcare engineering2021
Analysis on Health Information Acquisition of Social Network Users by Opinion Mining: Case Analysis Based on the Discussion on COVID-19 Vaccinations.
Article in Journal of healthcare engineering, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 7 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
7 citing papers in PubMed.
- An analysis of retracted COVID-19 articles published by one medical publisher with multiple journals.Proceedings (Baylor University. Medical Center) · 2024Article
- Applications of Social Media and Digital Technologies in COVID-19 Vaccination: Scoping Review.Journal of medical Internet research · 2023Article
- Retracted: Analysis on Health Information Acquisition of Social Network Users by Opinion Mining: Case Analysis Based on the Discussion on COVID-19 Vaccinations.Journal of healthcare engineering · 2023Article
- Article
- Social media and attitudes towards a COVID-19 vaccination: A systematic review of the literature.EClinicalMedicine · 2022Article
- Article
- Jordanian Patients' Family Members Need Perceptions in the Critical Care Settings: Nurses' Perspectives versus Family Members' Perspectives in the Context of Health Informatics.Journal of healthcare engineering · 2021Article
Corrections and comments
- Retraction · 2023-05-24Concerns/Issues about Data · Concerns/Issues about Referencing/Attributions · Concerns/Issues about Peer Review · Investigation by Journal/Publisher · Investigation by Third Party · Unreliable Results and/or Conclusions ·
- Retracted
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study aims to explore phenomena and laws that occur when different users on social network platforms obtain health information by constructing an opinion mining model, analyzing the user's position on selected cases, and exploring the reflection of the phenomenon of truth decay on platforms. It selects group posts regarding the COVID-19 vaccination dispute on the Douban platform, analyzes the positions of different users, and explores phenomena related to users obtaining health information on domestic social platforms according to different topics and information behaviors. The results reveal a linear relationship between the negative and neutral attitudes of netizens on social networking platforms. Moreover, netizens tend to hold subjective language when expressing their views and attitudes, and their views on social platforms will not change easily. The study explores the health information acquisition behavior of netizens on social platforms based on the constructed user opinion mining model. The study is helpful for relevant units and platforms to make scientific decisions and provide guidance according to different positions of Internet users.
Indexed as
Identifiers
What Socratic 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 Socratic graph.