Evidence map›Paper›PMID 28837664›Full record

ArticlePloS one2017

The unbearable emptiness of tweeting-About journal articles.

Nicolas Robinson-Garcia, Rodrigo Costas, Kimberley Isett, Julia Melkers, Diana Hicks

Abstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–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

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Observational
  5. Article
  6. Review
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Citations and science.International journal of clinical pharmacy · 2017
    Article
  15. 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.

Nicolas Robinson-GarciaINGENIO (CSIC-UPV), Universitat Politècnica de València, Valencia, Spain.ORCID http://orcid.org/0000-0002-0585-7359
Rodrigo CostasCentre for Science and Technology Studies (CWTS), Leiden University, Leiden, The Netherlands.
Kimberley IsettSchool of Public Policy, Georgia Institute of Technology, Atlanta, Georgia, United States.
Julia MelkersSchool of Public Policy, Georgia Institute of Technology, Atlanta, Georgia, United States.
Diana HicksSchool of Public Policy, Georgia Institute of Technology, Atlanta, Georgia, United States.

Funding

The National Dental PBRNU19DE022516 · NIDCR · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI GILBERT, GREGG H · 2012 to 2018
$66.4M
NIDCR NIH HHS U19 DE022516
6 · The paper itself

Abstract

Enthusiasm for using Twitter as a source of data in the social sciences extends to measuring the impact of research with Twitter data being a key component in the new altmetrics approach. In this paper, we examine tweets containing links to research articles in the field of dentistry to assess the extent to which tweeting about scientific papers signifies engagement with, attention to, or consumption of scientific literature. The main goal is to better comprehend the role Twitter plays in scholarly communication and the potential value of tweet counts as traces of broader engagement with scientific literature. In particular, the pattern of tweeting to the top ten most tweeted scientific dental articles and of tweeting by accounts is examined. The ideal that tweeting about scholarly articles represents curating and informing about state-of-the-art appears not to be realized in practice. We see much presumably human tweeting almost entirely mechanical and devoid of original thought, no evidence of conversation, tweets generated by monomania, duplicate tweeting from many accounts under centralized professional management and tweets generated by bots. Some accounts exemplify the ideal, but they represent less than 10% of tweets. Therefore, any conclusions drawn from twitter data is swamped by the mechanical nature of the bulk of tweeting behavior. In light of these results, we discuss the compatibility of Twitter with the research enterprise as well as some of the financial incentives behind these patterns.

Indexed as

PublishingSocial MediaJournal Impact Factor

Identifiers

PMID28837664
PMCPMC5570264

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.