Articles edited by more heterogeneous contributors are more balanced, indicating productive friction that counters polarization¶
Claim · All claims
Evidence · 1 study · reviewr2·q2
Currency · newest study 2018 · not yet checked against its sources · not reviewed by a person
Subclaims¶
Reading the evidence codes
q is the design tier, i the impact, n the sample, and the kind with its r
the rigour judged within that kind: what each code means.
This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.
q2 i? In the reported study, pro-alternative-medicine Wikipedia articles were more balanced when edited by heterogeneous contributors holding both pro and contra attitudes, suggesting diverse contributors help prevent polarization. → Peter Holtz & Joachim Kimmerle & Ulrike Cress 2018
Evidence¶
Peter Holtz & Joachim Kimmerle & Ulrike Cress 2018¶
Peter Holtz & Joachim Kimmerle & Ulrike Cress. (2018). Using big data techniques for measuring productive friction in mass collaboration online environments. Intern. J. Comput.-Support. Collab. Learn. https://doi.org/10.1007/s11412-018-9285-y
q2 · i? · review · r2
The review reports this from the same observational analysis of Wikipedia edit histories (Jirschitzka et al. 2017), where friction was operationalized as differences between authors' and articles' views. The articles the review attributes to Bakshy et al. and Del Vicario et al. frame the interpretation about echo chambers and polarization. No effect size is printed.
"In the case of pro alternative medicine articles, the articles were more balanced when they were edited by more heterogeneous contributors, that is, contributors who displayed both pro and contra alternative medicine attitudes."
Discussion¶
Related Claims¶
- Wikipedia contributors show confirmation bias by preferentially editing articles consistent with their own views — related
- New Wikipedia knowledge emerges around pivotal articles: high-centrality articles within domains and high-betweenness boundary-spanning articles between domains — related
- Three big data methods—text classification, cluster analysis, and social network analysis—can each yield insights into learning in mass collaboration — a broader claim this one bears on
- Wiki pages produced by many anonymous edits exhibit group-generated meaning not attributable to any individual contributor — related
- Politically charged framing (gun control ban) makes responses to the same data politically polarized and less accurate — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
heterogeneous-contributors-balance-articles |
title |
Articles edited by more heterogeneous contributors are more balanced, indicating productive friction that counters polarization |
description |
Articles edited by more heterogeneous contributors are more balanced, indicating productive friction that counters polarization |
status |
review |
evidence_strength |
weak |
newest_evidence |
2018 |
generated |
by process:wiki-ingest on 2026-10-18 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — peter-holtz-joachim-kimmerle-ulrike-cress-2018 |
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