Evidence map›Paper›PMID 27835703›Full record

ArticlePloS one2016

Twitter Predicts Citation Rates of Ecological Research.

Brandon K Peoples, Stephen R Midway, Dana Sackett, Abigail Lynch, Patrick B Cooney

Abstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

40 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. A memory-theoretic account of citation propagation.Royal Society open science · 2024
    Article
  5. Article
  6. The Effect of Open Access on Scholarly and Societal Metrics of Impact in the ASHA Journals.Journal of speech, language, and hearing research : JSLHR · 2023
    Article
  7. Article
  8. Article
  9. Article
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  11. Twitter integration of chemistry software tools.Journal of cheminformatics · 2021
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Where are all the anthelmintics? Challenges and opportunities on the path to new anthelmintics.International journal for parasitology. Drugs and drug resistance · 2020
    Article
  19. Observational
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Brandon K PeoplesDepartment of Forestry and Environmental Conservation, Clemson University, Clemson, South Carolina, United States of America.ORCID http://orcid.org/0000-0002-3954-4908
Stephen R MidwayDepartment of Oceanography and Coastal Sciences, Louisiana State University, Baton Rouge, Louisiana, United States of America.
Dana SackettSchool of Fisheries, Aquaculture, and Aquatic Sciences, Auburn University, Auburn, Alabama, United States of America.
Abigail LynchNational Climate Change and Wildlife Science Center, United States Geological Survey, Reston, Virginia, United States of America.
Patrick B CooneySmith-Root, Inc., Vancouver, Washington, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The relationship between traditional metrics of research impact (e.g., number of citations) and alternative metrics (altmetrics) such as Twitter activity are of great interest, but remain imprecisely quantified. We used generalized linear mixed modeling to estimate the relative effects of Twitter activity, journal impact factor, and time since publication on Web of Science citation rates of 1,599 primary research articles from 20 ecology journals published from 2012-2014. We found a strong positive relationship between Twitter activity (i.e., the number of unique tweets about an article) and number of citations. Twitter activity was a more important predictor of citation rates than 5-year journal impact factor. Moreover, Twitter activity was not driven by journal impact factor; the 'highest-impact' journals were not necessarily the most discussed online. The effect of Twitter activity was only about a fifth as strong as time since publication; accounting for this confounding factor was critical for estimating the true effects of Twitter use. Articles in impactful journals can become heavily cited, but articles in journals with lower impact factors can generate considerable Twitter activity and also become heavily cited. Authors may benefit from establishing a strong social media presence, but should not expect research to become highly cited solely through social media promotion. Our research demonstrates that altmetrics and traditional metrics can be closely related, but not identical. We suggest that both altmetrics and traditional citation rates can be useful metrics of research impact.

Indexed as

BibliometricsEcologyHumansJournal Impact FactorLinear ModelsPeriodicals as TopicSocial Media

Identifiers

PMID27835703
PMCPMC5106010

What OpenQuestion holds

Textmetadata
LicenceCC0
Read underepoch 390

Registered trials

None linked

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.