Evidence map›Paper›PMID 30335827›Full record

ArticlePloS one2018

The Why We Retweet scale.

Anuja Majmundar, Jon-Patrick Allem, Tess Boley Cruz, Jennifer Beth Unger

Abstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

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  9. The predictive utility of word familiarity for online engagements and funding.Proceedings of the National Academy of Sciences of the United States of America · 2021
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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

4 authors.

Anuja MajmundarKeck School of Medicine of USC, Los Angeles, CA, United States.ORCID 0000-0002-7785-3357
Jon-Patrick AllemKeck School of Medicine of USC, Los Angeles, CA, United States.
Tess Boley CruzKeck School of Medicine of USC, Los Angeles, CA, United States.ORCID 0000-0002-5894-1802
Jennifer Beth UngerKeck School of Medicine of USC, Los Angeles, CA, United States.

Funding

USC Tobacco Center of Regulatory ScienceU54CA180905 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI John R Monterosso · 2018 to 2026
$39.0M
USC Tobacco Center of Regulatory Science (TCORS) for Vulnerable PopulationsP50CA180905 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI PENTZ, MARY ANN, SAMET, JONATHAN M · 2013 to 2017
$20.1M
NCI NIH HHS P50 CA180905NCI NIH HHS U54 CA180905
6 · The paper itself

Abstract

backgroundTwitter offers a platform for rapid diffusion of information and its users' attitudes and behaviors. Insights about information propagation via retweets (the message forwarding function) offer observable explanations of ways in which modern human interactions get organized in the form of online networks, and contextualized in the form of public health, policy decisions, disaster management, and civic participation. This study conceptualized and validated the Why We Retweet Scale to contextualize retweeting behavior.

objectiveTwitter users were identified using clustering algorithms that consider a users' position in their network and invited for an online survey. Participants (N = 1433) responded to 19 questions about why they retweet. Exploratory factor Analysis (EFA) was conducted on a scale development sample (70% of original sample), which informed the Confirmatory Factor Analysis (CFA) on a scale testing sample (30% of the original sample). Varimax rotation was used to obtain a rotated factor solution, which resulted in interpretable factors. Demographic differences among scale factors were analyzed using one-way ANOVA or independent samples t-tests.

resultsThe final model (χ221 = 28, RMSEA = .03 [90% CI, 0.00-0.06], CFA = .99, TLI = 0.99) represented a parsimonious solution with 4 factors, measured by 2-3 items each, creating a final scale consisting of 9 items. Factor labels and definitions were: (1) Show approval, "Show support to the tweeter"; (2) Argue, "To argue against a tweet that I disagree with"; (3) Gain attention, "Add followers or gain attention"; and (4) Entertain, "Create humor/amusement". Demographic differences were also reported.

conclusionsThe Why We Retweet Scale offers a useful conceptualization and assessment of motivations for retweeting. In the future, communication strategists might consider the factors associated with information propagation when designing campaign messages to maximize message reach and engagement on Twitter.

Indexed as

Social MediaAdultEducational StatusFactor Analysis, StatisticalFemaleHumansIncomeMaleRacial GroupsReproducibility of ResultsSocial NetworkingSurveys and QuestionnairesYoung Adult

Identifiers

PMID30335827
PMCPMC6193720

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.