Evidence map›Paper›PMID 36576914›Full record

ArticlePloS one2022

Coming together in a digital age: Community twitter responses in the wake of a campus shooting.

Jessamyn Bowling, Erika Montanaro, Sarai Guerrero Ordonez, Sean McCabe, Shayna Farris, Neielle Saint-Cyr, Wade Glaser, Robert J Cramer, Jennifer Langhinrichsen-Rohling, Annelise Mennicke

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.9field-weighted citation impact, top 20% of its field
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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Surveillance of Gun-Related Conversations on Twitter.Prevention science : the official journal of the Society for Prevention Research · 2024
    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

10 authors at 2 institutions in 1 country.

Jessamyn BowlingUniversity of North Carolina at Charlotte, Charlotte, NC, United States of America.ORCID 0000-0001-7410-4433
Erika MontanaroUniversity of North Carolina at Charlotte, Charlotte, NC, United States of America.
Sarai Guerrero OrdonezUniversity of North Carolina at Charlotte, Charlotte, NC, United States of America.
Sean McCabeUniversity of North Carolina at Charlotte, Charlotte, NC, United States of America.
Shayna FarrisUniversity of North Carolina at Charlotte, Charlotte, NC, United States of America.
Neielle Saint-CyrUniversity of North Carolina at Charlotte, Charlotte, NC, United States of America.
Wade GlaserGaston Day School, Gastonia, NC, United States of America.
Robert J CramerUniversity of North Carolina at Charlotte, Charlotte, NC, United States of America.
Jennifer Langhinrichsen-RohlingUniversity of North Carolina at Charlotte, Charlotte, NC, United States of America.ORCID 0000-0002-3603-9201
Annelise MennickeUniversity of North Carolina at Charlotte, Charlotte, NC, United States of America.
University of North Carolina at Charlotte · USGaston Day School · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Campus mass shootings have become a pressing policy and public health matter. Twitter is a platform used for processing events among interested community members. Examining the responses of invested community members to a mass shooting on a college campus provides evidence for how this type of violence affects the immediate community and the larger public. These responses may reflect either content (e.g. context-specific) or emotions (e.g. humor). Aims Using Twitter data, we analyzed the emotional responses as well as the nature of non-affective short-term reactions, in response to the April 2019 shooting at UNC Charlotte. Methods Drawn from a pool of tweets between 4/30/19-5/7/19, we analyzed 16,749 tweets using keywords related to the mass shooting (e.g. "shooting," "gun violence," "UNC Charlotte"). A coding team manually coded the tweets using content and sentiment analyses. Results Overall, 7,148 (42.67%) tweets contained negative emotions (e.g. anger, sadness, disgust, anxiety), 5,088 (30.38%) contained positive emotions (e.g. humor, hope, appreciation), 14,892 (88.91%) were communal responses to the shooting (e.g. prayers, healing, victim remembrance), 8,329 (49.73%) were action-oriented (e.g. action taken, policy advocacy), and 15,498 (92.53%) included information (e.g. death/injury, news). All tweets except positive emotions peaked one day following the incident. Conclusions Our findings point to peaks in most emotions in the 24 hours following the event, with the exception of positive emotions which peaked one day later. Social media responses to a campus shooting suggest college preparedness for immediate deployment of supportive responses in the case of campus violence is needed.

Indexed as

Social MediaAngerAnxietyAnxiety DisordersEmotionsHumans

Identifiers

PMID36576914
PMCPMC9797086
OpenAlexW4313340167

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.