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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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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. |
format | Online Article Text |
id | pubmed-5360246 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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