Evidence map›Paper›PMID 38977803›Full record

ArticleScientific reports2024

In-party love spreads more efficiently than out-party hate in online communities.

Samuel Martin-Gutierrez, José Manuel Robles Morales, Mariano Torcal, Juan Carlos Losada, Rosa María Benito

Abstract read
In one paragraph

Article in Scientific reports, 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. 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.

Samuel Martin-GutierrezComplexity Science Hub Vienna, Josefstaedter Str. 39, 1080, Vienna, Austria. martin.gutierrez@csh.ac.at.ORCID 0000-0002-5685-7834
José Manuel Robles MoralesDepartment of Applied Sociology, Faculty of Political Sciences and Sociology, Universidad Complutense Madrid, Madrid, Spain.ORCID 0000-0003-1092-3864
Mariano TorcalDepartamento de Ciencias Políticas y Sociales, Universitat Pompeu Fabra, Trias Fargas 25-27, 08005, Barcelona, Spain.ORCID 0000-0002-0060-1522
Juan Carlos LosadaGrupo de Sistemas Complejos, ETSIAAB, Universidad Politécnica de Madrid, Av. Puerta de Hierro 2-4, 28040, Madrid, Spain.ORCID 0000-0002-4373-603X
Rosa María BenitoGrupo de Sistemas Complejos, ETSIAAB, Universidad Politécnica de Madrid, Av. Puerta de Hierro 2-4, 28040, Madrid, Spain.ORCID 0000-0003-3949-8232

Funding

Institució Catalana de Recerca i Estudis Avançats Intense Research AwardMinisterio de Ciencia e Innovación PID2019-106254RB-I00Ministerio de Ciencia e Innovación PID2021-122711NB-C21Ministerio de Ciencia, Innovación y Universidades PGC2018-093854-B-I00Ministerio de Educación, Cultura y Deporte FPU15/01461Österreichische Forschungsförderungsgesellschaft 873927
6 · The paper itself

Abstract

In this article, we present the findings of a comprehensive longitudinal social network analysis conducted on Twitter across four consecutive election campaigns in Spain, spanning from 2015 to 2019. Our focus is on the discernible trend of increasing partisan and ideological homogeneity within interpersonal exchanges on this social media platform, alongside high levels of networking efficiency measured through average retweeting. This diachronic study allows us to observe how dynamics of party competition might contribute to perpetuating and strengthening network ideological and partisan homophily, creating 'epistemic bubbles' in Twitter, yet showing a greater resistance to transforming them into 'partisan echo-chambers.' Specifically, our analysis reveals that the rise of a new radical right-wing party (RRP), Vox, has heightened ideological homogeneity among users across the entire ideological spectrum. However, this process has not been uniform. While users aligned with mainstream political parties consistently share content that reinforces in-party affinity, resulting in highly efficient 'epistemic bubbles,' the emergence of the RRP has given rise to a distinct group of users associated with the most extreme partisan positions, characterized by a notable proportion of out-partisan hostility content, which has fostered the creation of low-efficient 'partisan echo-chambers.'

Indexed as

PoliticsSocial MediaHateHumansLoveSocial Network AnalysisSocial NetworkingSpainEpistemic bubblesIn-party affinityOut-party hostilityPartisan echo-chambersParty supplyPolarizationRetweetingTwitter

Identifiers

PMID38977803
PMCPMC11231175

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.