The COVID-19 infodemic is driven partially by Twitter bots. Flagging bot accounts and the misinformation they share could provide one strategy for preventing the spread of false information online. This article reports on an experiment ( = 299) conducted with participants in the USA to see whether flagging tweets as coming from bot accounts and as containing misinformation can lower participants' self-reported engagement and attitudes about the tweets. This experiment also showed participants tweets that aligned with their previously held beliefs to determine how flags affect their overall opinions. Results showed that flagging tweets lowered participants' attitudes about them, though this effect was less pronounced in participants who frequently used social media or consumed more news, especially from Facebook or Fox News. Some participants also changed their opinions after seeing the flagged tweets. The results suggest that social media companies can flag suspicious or inaccurate content as a way to fight misinformation. Flagging could be built into future automated fact-checking systems and other misinformation abatement strategies of the social network analysis and mining community.
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http://dx.doi.org/10.1007/s13278-021-00739-x | DOI Listing |
JMIR Infodemiology
January 2025
Computational Social Science DataLab, University Institute of Research for Sustainable Social Development (INDESS), University of Cadiz, Jerez de la Frontera, Spain.
Background: During the COVID-19 pandemic, social media platforms have been a venue for the exchange of messages, including those related to fake news. There are also accounts programmed to disseminate and amplify specific messages, which can affect individual decision-making and present new challenges for public health.
Objective: This study aimed to analyze how social bots use hashtags compared to human users on topics related to misinformation during the outbreak of the COVID-19 pandemic.
Orphanet J Rare Dis
November 2024
Department of Public Health and Primary Care, Leiden University Medical Center, Postzone V0-P, PO Box 9600, 2300 RC, Leiden, The Netherlands.
Invest Ophthalmol Vis Sci
November 2024
Centre for Vision and Eye Research, Faculty of Health, Queensland University of Technology, Brisbane, Queensland, Australia.
Purpose: The purpose of this study was to assess fine motor skills and reading proficiency in adults with amblyopia and/or strabismus, and to determine how these relate to clinical measures of vision and self-reported vision-related quality of life.
Methods: Fine motor skills (Manual dexterity - Bruininks-Oseretsky Test of Motor Proficiency [BOT-2]) and reading performance (International Reading Speed Texts [IReST]) were assessed in 23 adults with non-strabismic amblyopia, 20 with non-amblyopic strabismus, 52 with both amblyopia and strabismus, and 19 with normal visual development. Visual acuity and binocular function score (BFS), obtained from stereoacuity and presence/absence of suppression, were also determined.
J Exp Bot
November 2024
ARC Centre of Excellence in Plant Energy Biology, Research School of Biology, The Australian National University, Canberra, ACT 2601, Australia.
An approach to improving radiation use efficiency (RUE) in wheat is to screen for variability in rates of leaf respiration in darkness (Rdark). We used a high-throughput system to quantify variation in Rdark among a diverse range of spring wheat genotypes (301 lines) grown in two countries (Mexico and Australia) and two seasons (2017 and 2018), and in doing so quantify the relative importance of genotype (G) and environment (E) in influencing variations in leaf Rdark. Through careful design, residual (unexplained) variation represented less than 10% of the total observed.
View Article and Find Full Text PDFJ Exp Bot
November 2024
The Robert H. Smith Institute of Plant Sciences and Genetics in Agriculture, Faculty of Agriculture, Hebrew University of Jerusalem.
Rising winter temperatures jeopardize the fruit yield of trees that require a prolonged and sufficiently cold winter to flower. Predicting the exact risk to different crop varieties is the first step in mitigating the harmful effects of climate change. This work focused on olive (Olea europaea) - a traditional crop in the Mediterranean basin whose flowering depends on the sufficiency of cold periods and the lack of warm ones during the preceding winter.
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