Immunology and social networks: an approach towards impact assessment
Scientific journals have changed the mechanisms they use for distribution and dissemination of information. Different approaches towards determining impact have emerged and among these, metrics derived from activity on social media are an emerging trend. This article aims to assess whether a correlation exists between the traditional impact factor and activity on social media. We assessed journals categorized within the area of “immunology” on the SCImago Journal and Country Rank website. Variables reflecting traditional and alternative measures of impact were collected. Differences between journals with and without social networks were assessed using non-parametric Mann–Whitney U tests. Correlation was assessed through Spearman tests. 156 journals were analyzed, 17% had at least one social network. 48.2% of journals with social networks were classified within SJR’s quartile 1. An almost perfect correlation was found between the SJR and the number of followers on Twitter, this correlation remained statistically significant after adjusting for time since creation of the account [Spearman’s correlation (rs) = 0.83]. We propose the use of Twitter as a mechanism for dissemination of information by immunology journals, as well as other social networks for their potential to increase their audience, as well as the dissemination and impact of their publications.
KeywordsImmunology Social networks Impact factor Mass media Social media
JAO and JMO: acquisition, and interpretation of data for the work, drafting the work, final approval of the version to be published, and agreed to be accountable for all aspects of the work; DGF: conception and design, and interpretation of data for the work, drafting the work, final approval of the version to be published and agreed to be accountable for all aspects of the work; DP: acquisition, and interpretation of data for the work, design and drafting of the work, final approval of the version to be published and agreed to be accountable for all aspects of the work.
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflicts of interest.
The ethics and research committee of our institution approved the study protocol.
Research involving human participants
This article does not contain any studies with human participants or animals performed by any of the authors.
- 2.SCImago (n.d.) (2019) SJR—SCImago Journal & Country Rank [Portal]. http://www.scimagojr.com
- 3.Gonzalez-Pereira B, Guerrero-Bote V, Moya-Anegon F (2009) The SJR indicator: a new indicator of journals’ scientific prestige. ArXiv09124141 PhysGoogle Scholar
- 5.Altmetrics: a manifesto—altmetrics.org. http://altmetrics.org/manifesto/. Accessed 25 Jun 2019
- 6.Mozhdeh S, Sareh D (2019) Comparing the citations counts and altmetrics of the top medical science journals in scopus. Int J Inf Sci Manag 17:59–72Google Scholar
- 7.Konkiel S Altmetrics: A 21st Century Solution to Determining Research Quality. In: Online Search. http://www.infotoday.com/OnlineSearcher/
- 8.Puschmann C (2014) (Micro)Blogging science? Notes on potentials and constraints of new forms of scholarly communication. In: Bartling S, Friesike S (eds) Opening science: the evolving guide on how the internet is changing research, collaboration and scholarly publishing. Springer International Publishing, Cham, pp 89–106CrossRefGoogle Scholar
- 9.Fox S, Duggan M (2013) Health Online 2013. In: Pew Res. Cent. https://www.pewinternet.org/2013/01/15/health-online-2013/
- 12.Muñoz-Velandia OM, Fernández-Ávila DG, Patino-Hernandez D, Gómez AM (2019) Metrics of activity in social networks are correlated with traditional metrics of scientific impact in endocrinology journals. Diabetes Metab Syndr Clin Res Rev. https://doi.org/10.1016/j.dsx.2019.06.018 CrossRefGoogle Scholar