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The detection and effect of social events on Wikipedia data-set for studying human preferences
Several studies have used Wikipedia (WP) data-set to analyse worldwide human preferences by languages. However, those studies could suffer from bias related to exceptional social circumstances. Any massive event promoting exceptional editions of WP can be defined as a source of bias. In this article...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10098102/ https://www.ncbi.nlm.nih.gov/pubmed/37063484 http://dx.doi.org/10.3389/fdata.2023.1077318 |
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author | Assuied, Julien Gandica, Yérali |
author_facet | Assuied, Julien Gandica, Yérali |
author_sort | Assuied, Julien |
collection | PubMed |
description | Several studies have used Wikipedia (WP) data-set to analyse worldwide human preferences by languages. However, those studies could suffer from bias related to exceptional social circumstances. Any massive event promoting exceptional editions of WP can be defined as a source of bias. In this article, we follow a procedure for detecting outliers. Our study is based on 12 languages and 13 different categories. Our methodology defines a parameter, which is language-dependent instead of being externally fixed. We also study the presence of human cyclic behavior to evaluate apparent outliers. After our analysis, we found that the outliers in our data-set do not significantly affect the analysis of preferences by categories among different WP languages. While investigating the possibility of bias related to exceptional social circumstances is always a safe measure before doing any analysis on Big Data, we found that in the case of the first ten years of the Wikipedia data-set, outliers do not significantly affect using Wikipedia data-set as a digital footprint to analyse worldwide human preferences. |
format | Online Article Text |
id | pubmed-10098102 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-100981022023-04-14 The detection and effect of social events on Wikipedia data-set for studying human preferences Assuied, Julien Gandica, Yérali Front Big Data Big Data Several studies have used Wikipedia (WP) data-set to analyse worldwide human preferences by languages. However, those studies could suffer from bias related to exceptional social circumstances. Any massive event promoting exceptional editions of WP can be defined as a source of bias. In this article, we follow a procedure for detecting outliers. Our study is based on 12 languages and 13 different categories. Our methodology defines a parameter, which is language-dependent instead of being externally fixed. We also study the presence of human cyclic behavior to evaluate apparent outliers. After our analysis, we found that the outliers in our data-set do not significantly affect the analysis of preferences by categories among different WP languages. While investigating the possibility of bias related to exceptional social circumstances is always a safe measure before doing any analysis on Big Data, we found that in the case of the first ten years of the Wikipedia data-set, outliers do not significantly affect using Wikipedia data-set as a digital footprint to analyse worldwide human preferences. Frontiers Media S.A. 2023-03-30 /pmc/articles/PMC10098102/ /pubmed/37063484 http://dx.doi.org/10.3389/fdata.2023.1077318 Text en Copyright © 2023 Assuied and Gandica. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Big Data Assuied, Julien Gandica, Yérali The detection and effect of social events on Wikipedia data-set for studying human preferences |
title | The detection and effect of social events on Wikipedia data-set for studying human preferences |
title_full | The detection and effect of social events on Wikipedia data-set for studying human preferences |
title_fullStr | The detection and effect of social events on Wikipedia data-set for studying human preferences |
title_full_unstemmed | The detection and effect of social events on Wikipedia data-set for studying human preferences |
title_short | The detection and effect of social events on Wikipedia data-set for studying human preferences |
title_sort | detection and effect of social events on wikipedia data-set for studying human preferences |
topic | Big Data |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10098102/ https://www.ncbi.nlm.nih.gov/pubmed/37063484 http://dx.doi.org/10.3389/fdata.2023.1077318 |
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