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Understanding and coping with extremism in an online collaborative environment: A data-driven modeling

The Internet has provided us with great opportunities for large scale collaborative public good projects. Wikipedia is a predominant example of such projects where conflicts emerge and get resolved through bottom-up mechanisms leading to the emergence of the largest encyclopedia in human history. Di...

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Detalles Bibliográficos
Autores principales: Rudas, Csilla, Surányi, Olivér, Yasseri, Taha, Török, János
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5360246/
https://www.ncbi.nlm.nih.gov/pubmed/28323867
http://dx.doi.org/10.1371/journal.pone.0173561
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author Rudas, Csilla
Surányi, Olivér
Yasseri, Taha
Török, János
author_facet Rudas, Csilla
Surányi, Olivér
Yasseri, Taha
Török, János
author_sort Rudas, Csilla
collection PubMed
description The Internet has provided us with great opportunities for large scale collaborative public good projects. Wikipedia is a predominant example of such projects where conflicts emerge and get resolved through bottom-up mechanisms leading to the emergence of the largest encyclopedia in human history. Disaccord arises whenever editors with different opinions try to produce an article reflecting a consensual view. The debates are mainly heated by editors with extreme views. Using a model of common value production, we show that the consensus can only be reached if groups with extreme views can actively take part in the discussion and if their views are also represented in the common outcome, at least temporarily. We show that banning problematic editors mostly hinders the consensus as it delays discussion and thus the whole consensus building process. To validate the model, relevant quantities are measured both in simulations and Wikipedia, which show satisfactory agreement. We also consider the role of direct communication between editors both in the model and in Wikipedia data (by analyzing the Wikipedia talk pages). While the model suggests that in certain conditions there is an optimal rate of “talking” vs “editing”, it correctly predicts that in the current settings of Wikipedia, more activity in talk pages is associated with more controversy.
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spelling pubmed-53602462017-04-06 Understanding and coping with extremism in an online collaborative environment: A data-driven modeling Rudas, Csilla Surányi, Olivér Yasseri, Taha Török, János PLoS One Research Article The Internet has provided us with great opportunities for large scale collaborative public good projects. Wikipedia is a predominant example of such projects where conflicts emerge and get resolved through bottom-up mechanisms leading to the emergence of the largest encyclopedia in human history. Disaccord arises whenever editors with different opinions try to produce an article reflecting a consensual view. The debates are mainly heated by editors with extreme views. Using a model of common value production, we show that the consensus can only be reached if groups with extreme views can actively take part in the discussion and if their views are also represented in the common outcome, at least temporarily. We show that banning problematic editors mostly hinders the consensus as it delays discussion and thus the whole consensus building process. To validate the model, relevant quantities are measured both in simulations and Wikipedia, which show satisfactory agreement. We also consider the role of direct communication between editors both in the model and in Wikipedia data (by analyzing the Wikipedia talk pages). While the model suggests that in certain conditions there is an optimal rate of “talking” vs “editing”, it correctly predicts that in the current settings of Wikipedia, more activity in talk pages is associated with more controversy. Public Library of Science 2017-03-21 /pmc/articles/PMC5360246/ /pubmed/28323867 http://dx.doi.org/10.1371/journal.pone.0173561 Text en © 2017 Rudas et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Rudas, Csilla
Surányi, Olivér
Yasseri, Taha
Török, János
Understanding and coping with extremism in an online collaborative environment: A data-driven modeling
title Understanding and coping with extremism in an online collaborative environment: A data-driven modeling
title_full Understanding and coping with extremism in an online collaborative environment: A data-driven modeling
title_fullStr Understanding and coping with extremism in an online collaborative environment: A data-driven modeling
title_full_unstemmed Understanding and coping with extremism in an online collaborative environment: A data-driven modeling
title_short Understanding and coping with extremism in an online collaborative environment: A data-driven modeling
title_sort understanding and coping with extremism in an online collaborative environment: a data-driven modeling
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5360246/
https://www.ncbi.nlm.nih.gov/pubmed/28323867
http://dx.doi.org/10.1371/journal.pone.0173561
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