ArticlePloS one2019
Towards a second generation of 'social media metrics': Characterizing Twitter communities of attention around science.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
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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.
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Who cites it
18 citing papers in PubMed.
- Global research status and trends of compulsive sexual behavior disorder: A comprehensive bibliometric analysis.Journal of behavioral addictions · 2025Review
- Impact of a Fulbright award: A bibliometric analysis of persistence.Health SA = SA Gesondheid · 2025Article
- Knowledge Mapping of Macrophages in Osteoporosis: A Bibliometric Analysis (1999-2023).Orthopaedic surgery · 2024Review
- Article
- Monitoring Open Science as transformative change: Towards a systemic framework.F1000Research · 2024Article
- A role for qualitative methods in researching Twitter data on a popular science article's communication.Frontiers in research metrics and analytics · 2024Article
- Impact of #PsychTwitter in promoting global psychiatry: A hashtag analysis study.Frontiers in public health · 2023Article
- Evaluative altmetrics: is there evidence for its application to research evaluation?Frontiers in research metrics and analytics · 2023Article
- Are patents linked on Twitter? A case study of Google patents.Scientometrics · 2022Article
- What Does Twitter Say About Self-Regulated Learning? Mapping Tweets From 2011 to 2021.Frontiers in psychology · 2022Article
- Are automated accounts driving scholarly communication on Twitter? a case study of dissemination of COVID-19 publications.Scientometrics · 2022Article
- Who tweets climate change papers? investigating publics of research through users' descriptions.PloS one · 2022Article
- Article
- Lessons for science and technology policy? Probing the Linkedin network of an RDI organisation.SN social sciences · 2022Article
- Sense and Sensibility: Characterizing Social Media Users Regarding the Use of Controversial Terms for COVID-19.IEEE transactions on big data · 2021Article
- The world needs our science: broadening the research pipeline in anesthesiology.Regional anesthesia and pain medicine · 2021Article
- Quantifying and contextualizing the impact of bioRxiv preprints through automated social media audience segmentation.PLoS biology · 2020Article
- Social media and the modern scientist: a research primer for low- and middle-income countries.African journal of emergency medicine : Revue africaine de la medecine d'urgence · 2020Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
'Social media metrics' are bursting into science studies as emerging new measures of impact related to scholarly activities. However, their meaning and scope as scholarly metrics is still far from being grasped. This research seeks to shift focus from the consideration of social media metrics around science as mere indicators confined to the analysis of the use and visibility of publications on social media to their consideration as metrics of interaction and circulation of scientific knowledge across different communities of attention, and particularly as metrics that can also be used to characterize these communities. Although recent research efforts have proposed tentative typologies of social media users, no study has empirically examined the full range of Twitter user's behavior within Twitter and disclosed the latent dimensions in which activity on Twitter around science can be classified. To do so, we draw on the overall activity of social media users on Twitter interacting with research objects collected from the Altmetic.com database. Data from over 1.3 million unique users, accounting for over 14 million tweets to scientific publications, is analyzed. Based on an exploratory and confirmatory factor analysis, four latent dimensions are identified: 'Science Engagement', 'Social Media Capital', 'Social Media Activity' and 'Science Focus'. Evidence on the predominant type of users by each of the four dimensions is provided by means of VOSviewer term maps of Twitter profile descriptions. This research breaks new ground for the systematic analysis and characterization of social media users' activity around science.
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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.