Evidence map›Paper›PMID 40839684›Full record

ArticlePloS one2025

How language, culture, and geography shape online dialogue: Insights from Koo.

Amin Mekacher, Max Falkenberg, Andrea Baronchelli

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Amin MekacherDepartment of Mathematics, City St George's, London, United Kingdom.
Max FalkenbergDepartment of Network and Data Science, Central European University, Vienna, Austria.ORCID https://orcid.org/0000-0002-2986-2494
Andrea BaronchelliDepartment of Mathematics, City St George's, London, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Founded in India in 2020, the microblogging site 'Koo' launched as an alternative to mainstream social media platforms, with the explicit aim of catering to non-Western communities in their vernacular languages, and capitalising on a period of tension between the Indian government and Twitter which led many users to seek Twitter-alternatives. Drawing on a near-complete dataset totalling over 71M posts and 399M user interactions, we show how Koo attracted users from several countries including India, Nigeria and Brazil, but with variable levels of sustained user engagement. We highlight how Koo's interaction network was shaped by multiple country-specific migrations displaying strong divides between linguistic and cultural communities, for instance, with English-speaking communities from India and Nigeria largely isolated from one another. Finally, we analyse the content shared by different linguistic communities and identify cultural patterns which, we speculate, promoted similar discourses across language groups. Our results show that for language groups of similar sizes, Indian languages fostered higher discourse diversity than non-Indian languages, possibly highlighting synergistic effects which boosted the uptake and retention of these groups. Despite this, Koo failed to capitalise on this synergy and ceased operations in July 2024. With this context, our study points to some of the possible reasons why the multilingual and politically diverse platform Koo struggled to remain sustainable, failing to stave off competition from its US-based competitors, despite its commitment to cultivating support for the different vernacular communities of Indian social media users.

Indexed as

CultureLanguageSocial MediaBrazilGeographyHumansIndiaNigeria

Identifiers

PMID40839684
PMCPMC12370020

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.