Evidence map›Paper›PMID 42032032›Full record

ArticleScientific reports2026

From toxicity to conformity: adaptive user behavior to social norms in Telegram communities.

Lorenzo Alvisi, Victoria Popa, Guglielmo Cola, Serena Tardelli, Maurizio Tesconi

Abstract read
In one paragraph

Article in Scientific reports, 2026. 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. Review
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.

Lorenzo Alvisi *Institute of Informatics and Telematics, National Research Council, Pisa, Italy.
Victoria Popa *Institute of Informatics and Telematics, National Research Council, Pisa, Italy. victoria.popa@phd.unipi.it.
Guglielmo ColaInstitute of Informatics and Telematics, National Research Council, Pisa, Italy.
Serena TardelliInstitute of Informatics and Telematics, National Research Council, Pisa, Italy.
Maurizio TesconiInstitute of Informatics and Telematics, National Research Council, Pisa, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Toxic and antisocial user behavior on social media platforms has received considerable scholarly attention due to its detrimental effects on society. This study takes a holistic perspective on the phenomenon of online toxicity by investigating the impact of local community norms on toxic expression. By using six large-scale datasets, comprising over 500 million Telegram messages collected between 2015 and 2024, we analyze toxic user behavior across multiple chats and languages. We introduce a methodological framework that uses a conformity index to characterize conformist, anti-conformist, and independent behavioral tendencies. Our findings show that most users tend to conform to local normative environments, aligning their toxicity with the toxicity levels of the chats in which they participate. This pattern is consistent across datasets and languages, showing a strong association between community norms and user behavior online. Furthermore, we observe that higher levels of user participation in chats are associated with a stronger tendency toward conformity with the surrounding social contexts. Collectively, these findings contribute to a deeper understanding of toxic online behavior and highlight the importance of contextualized approaches to content moderation.

Indexed as

Social ConformitySocial MediaSocial NormsDigital MediaHumansSocial Group

Identifiers

PMID42032032
PMCPMC13276170

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.