Evidence map›Paper›PMID 35139109›Full record

ArticlePloS one2022

Users' polarisation in dynamic discussion networks: The case of refugee crisis in Sweden.

Elizaveta Kopacheva, Victoria Yantseva

Abstract readHistorical Article
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 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

2 authors.

Elizaveta KopachevaDepartment of Political Science & Centre for Data Intensive Sciences and Applications (DISA), Linnaeus University, Växjö, Sweden.ORCID 0000-0002-3708-6333
Victoria YantsevaDepartment of Social Studies & Centre for Data Intensive Sciences and Applications (DISA), Linnaeus University, Växjö, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper presents a study on the dynamics of sentiment polarisation in the active online discussion communities formed around a controversial topic-immigration. Using a collection of tweets in the Swedish language from 2012 to 2019, we track the development of the communities and their sentiment polarisation trajectories over time and in the context of an exogenous shock represented by the European refugee crisis in 2015. To achieve the goal of the study, we apply methods of network and sentiment analysis to map users' interactions in the network communities and quantify users' sentiment polarities. The results of the analysis give little evidence for users' polarisation in the network and its communities, as well as suggest that the crisis had a limited effect on the polarisation dynamics on this social media platform. Yet, we notice a shift towards more negative tonality of users' sentiments after the crisis and discuss possible explanations for the above-mentioned observations.

Indexed as

AttitudeAggressionDatasets as TopicEmigration and ImmigrationGroup ProcessesHistory, 20th CenturyHistory, 21st CenturyHumansPublic OpinionRefugeesSentiment AnalysisSocial IdentificationSocial MediaSocial Network AnalysisSweden

Identifiers

PMID35139109
PMCPMC8827437

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.