Evidence map›Paper›PMID 36170276›Full record

ArticlePloS one2022

Understanding the expression of loneliness on Twitter across age groups and genders.

Anietie Andy, Garrick Sherman, Sharath Chandra Guntuku

Abstract 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 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.

  1. Digital phenotyping and ASCVD risk: An exploratory cross-sectional analysis using online behavioral data.American heart journal plus : cardiology research and practice · 2026
    Article
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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

3 authors.

Anietie AndyPenn Medicine, University of Pennsylvania, Philadelphia, PA, United States of America.ORCID 0000-0002-7043-3042
Garrick ShermanComputer and Information Science, University of Pennsylvania, Philadelphia, PA, United States of America.
Sharath Chandra GuntukuComputer and Information Science, University of Pennsylvania, Philadelphia, PA, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Some individuals seek support around loneliness on social media forums. In this work, we aim to determine differences in the use of language by users-in different age groups and genders (female, male), who publish posts on Twitter expressing loneliness. We hypothesize that these differences in the use of language will reflect how these users express themselves and some of their support needs. Interventions may vary depending on the age and gender of an individual, hence, in order to identify high-risk individuals who express loneliness on Twitter and provide appropriate interventions for these users, it is important to understand the variations in language use by users who belong to different age groups and genders and post about loneliness on Twitter. We discuss the findings from this work and how they can help guide the design of online loneliness interventions.

Indexed as

LonelinessSocial MediaFemaleHumansLanguageMale

Identifiers

PMID36170276
PMCPMC9518878

What OpenQuestion holds

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LicenceCC BY
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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.