Evidence map›Paper›PMID 39325247›Full record

ArticleJournal of urban health : bulletin of the New York Academy of Medicine2024

Sentiment Analysis of Twitter Posts Related to a COVID-19 Test & Trace Program in NYC.

Krystle A Tsai, Michelle M Chau, Juncheng Wang, Lorna E Thorpe, Rachel E Massar, Sarah Conderino, Carolyn A Berry, Nadia S Islam, Anna Bershteyn, Marie A Bragg

Abstract read
In one paragraph

Article in Journal of urban health : bulletin of the New York Academy of Medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Krystle A TsaiDepartment of Population Health, NYU Grossman School of Medicine, 180 Madison Ave, New York, NY, 110016, USA.
Michelle M ChauDepartment of Population Health, NYU Grossman School of Medicine, 180 Madison Ave, New York, NY, 110016, USA.
Juncheng WangDepartment of Population Health, NYU Grossman School of Medicine, 180 Madison Ave, New York, NY, 110016, USA.
Lorna E ThorpeDepartment of Population Health, NYU Grossman School of Medicine, 180 Madison Ave, New York, NY, 110016, USA.
Rachel E MassarDepartment of Population Health, NYU Grossman School of Medicine, 180 Madison Ave, New York, NY, 110016, USA.
Sarah ConderinoDepartment of Population Health, NYU Grossman School of Medicine, 180 Madison Ave, New York, NY, 110016, USA.
Carolyn A BerryDepartment of Population Health, NYU Grossman School of Medicine, 180 Madison Ave, New York, NY, 110016, USA.
Nadia S IslamDepartment of Population Health, NYU Grossman School of Medicine, 180 Madison Ave, New York, NY, 110016, USA.
Anna BershteynDepartment of Population Health, NYU Grossman School of Medicine, 180 Madison Ave, New York, NY, 110016, USA.
Marie A BraggDepartment of Population Health, NYU Grossman School of Medicine, 180 Madison Ave, New York, NY, 110016, USA. marie.bragg@nyulangone.org.ORCID http://orcid.org/0000-0002-6858-7173

Funding

NYC Health and Human Services 1007645
6 · The paper itself

Abstract

As part of a program evaluation of the New York City Test & Trace program (T2)-one of the largest such programs in the USA-we conducted a study to assess how implementing organizations (NYC Health + Hospitals, government agencies, CBOs) communicated information about the T2 program on Twitter. Study aims were as follows: (1) quantify user engagement of posts ("tweets") about T2 by NYC organizations on Twitter and (2) examine the emotional tone of social media users' T2-related tweets in our sample of 1987 T2-related tweets. Celebrities and CBOs generated more user engagement (0.26% and 0.07%, respectively) compared to government agencies (e.g., Mayor's Office, 0.0019%), reinforcing the value of collaborating with celebrities and CBOs in social media public health campaigns. Sentiment analysis revealed that positive tweets (46.5%) had higher user engagement than negative tweets (number of likes: R

Indexed as

COVID-19Social MediaCOVID-19 TestingHealth PromotionHumansInformation DisseminationNew York CityProgram EvaluationSARS-CoV-2

Identifiers

PMID39325247
PMCPMC11461426

What OpenQuestion holds

Textmetadata
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.