Weather impacts expressed sentiment

We conduct the largest ever investigation into the relationship between meteorological conditions and the sentiment of human expressions. To do this, we employ over three and a half billion social media posts from tens of millions of individuals from both Facebook and Twitter between 2009 and 2016....

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Detalles Bibliográficos
Autores principales: Baylis, Patrick, Obradovich, Nick, Kryvasheyeu, Yury, Chen, Haohui, Coviello, Lorenzo, Moro, Esteban, Cebrian, Manuel, Fowler, James H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5918636/
https://www.ncbi.nlm.nih.gov/pubmed/29694424
http://dx.doi.org/10.1371/journal.pone.0195750
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author Baylis, Patrick
Obradovich, Nick
Kryvasheyeu, Yury
Chen, Haohui
Coviello, Lorenzo
Moro, Esteban
Cebrian, Manuel
Fowler, James H.
author_facet Baylis, Patrick
Obradovich, Nick
Kryvasheyeu, Yury
Chen, Haohui
Coviello, Lorenzo
Moro, Esteban
Cebrian, Manuel
Fowler, James H.
author_sort Baylis, Patrick
collection PubMed
description We conduct the largest ever investigation into the relationship between meteorological conditions and the sentiment of human expressions. To do this, we employ over three and a half billion social media posts from tens of millions of individuals from both Facebook and Twitter between 2009 and 2016. We find that cold temperatures, hot temperatures, precipitation, narrower daily temperature ranges, humidity, and cloud cover are all associated with worsened expressions of sentiment, even when excluding weather-related posts. We compare the magnitude of our estimates with the effect sizes associated with notable historical events occurring within our data.
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spelling pubmed-59186362018-05-05 Weather impacts expressed sentiment Baylis, Patrick Obradovich, Nick Kryvasheyeu, Yury Chen, Haohui Coviello, Lorenzo Moro, Esteban Cebrian, Manuel Fowler, James H. PLoS One Research Article We conduct the largest ever investigation into the relationship between meteorological conditions and the sentiment of human expressions. To do this, we employ over three and a half billion social media posts from tens of millions of individuals from both Facebook and Twitter between 2009 and 2016. We find that cold temperatures, hot temperatures, precipitation, narrower daily temperature ranges, humidity, and cloud cover are all associated with worsened expressions of sentiment, even when excluding weather-related posts. We compare the magnitude of our estimates with the effect sizes associated with notable historical events occurring within our data. Public Library of Science 2018-04-25 /pmc/articles/PMC5918636/ /pubmed/29694424 http://dx.doi.org/10.1371/journal.pone.0195750 Text en © 2018 Baylis et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://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
Baylis, Patrick
Obradovich, Nick
Kryvasheyeu, Yury
Chen, Haohui
Coviello, Lorenzo
Moro, Esteban
Cebrian, Manuel
Fowler, James H.
Weather impacts expressed sentiment
title Weather impacts expressed sentiment
title_full Weather impacts expressed sentiment
title_fullStr Weather impacts expressed sentiment
title_full_unstemmed Weather impacts expressed sentiment
title_short Weather impacts expressed sentiment
title_sort weather impacts expressed sentiment
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5918636/
https://www.ncbi.nlm.nih.gov/pubmed/29694424
http://dx.doi.org/10.1371/journal.pone.0195750
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AT moroesteban weatherimpactsexpressedsentiment
AT cebrianmanuel weatherimpactsexpressedsentiment
AT fowlerjamesh weatherimpactsexpressedsentiment

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