Evidence map›Paper›PMID 33852612›Full record

ArticlePloS one2021

Ratioing the President: An exploration of public engagement with Obama and Trump on Twitter.

Joshua R Minot, Michael V Arnold, Thayer Alshaabi, Christopher M Danforth, Peter Sheridan Dodds

Abstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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.

Joshua R MinotDepartment of Mathematics and Statistics, University of Vermont, Burlington, VT, United States of America.ORCID 0000-0002-6244-8586
Michael V ArnoldDepartment of Mathematics and Statistics, University of Vermont, Burlington, VT, United States of America.
Thayer AlshaabiDepartment of Mathematics and Statistics, University of Vermont, Burlington, VT, United States of America.
Christopher M DanforthDepartment of Mathematics and Statistics, University of Vermont, Burlington, VT, United States of America.
Peter Sheridan DoddsDepartment of Mathematics and Statistics, University of Vermont, Burlington, VT, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The past decade has witnessed a marked increase in the use of social media by politicians, most notably exemplified by the 45th President of the United States (POTUS), Donald Trump. On Twitter, POTUS messages consistently attract high levels of engagement as measured by likes, retweets, and replies. Here, we quantify the balance of these activities, also known as "ratios", and study their dynamics as a proxy for collective political engagement in response to presidential communications. We find that raw activity counts increase during the period leading up to the 2016 election, accompanied by a regime change in the ratio of retweets-to-replies connected to the transition between campaigning and governing. For the Trump account, we find words related to fake news and the Mueller inquiry are more common in tweets with a high number of replies relative to retweets. Finally, we find that Barack Obama consistently received a higher retweet-to-reply ratio than Donald Trump. These results suggest Trump's Twitter posts are more often controversial and subject to enduring engagement as a given news cycle unfolds.

Indexed as

CommunicationPoliticsSocial MediaHumansUnited States

Identifiers

PMID33852612
PMCPMC8046224

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.