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Inter-City Emotional Synchrony Is Conditional on Mobility Patterns

Recent research has attempted to document large-scale emotional contagion on online social networks. Despite emotional contagion being primarily driven by in-person mechanisms, less research has attempted to measure large-scale emotional contagion in in-person contexts. In this paper, I operationali...

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Detalles Bibliográficos
Autor principal: Vachuska, Karl
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9687524/
https://www.ncbi.nlm.nih.gov/pubmed/36354387
http://dx.doi.org/10.3390/bs12110410
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author Vachuska, Karl
author_facet Vachuska, Karl
author_sort Vachuska, Karl
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description Recent research has attempted to document large-scale emotional contagion on online social networks. Despite emotional contagion being primarily driven by in-person mechanisms, less research has attempted to measure large-scale emotional contagion in in-person contexts. In this paper, I operationalize the temporal emotions associated with a particular city at particular points in time using sentiment analysis on Twitter data. Subsequently, I study how emotions converge between seven proximal cities in the state of Virginia, using two-way fixed effect models. I find that positive emotions tend to be synchronous between cities, but that effect is conditional on the level of contact between city residents at that period of time, as indicated by cell phone mobility data. I do not find any synchrony based on other types of emotions or general sentiment. I discourage drawing causal conclusions based on the presumed existence of several unmeasured sources of bias.
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spelling pubmed-96875242022-11-25 Inter-City Emotional Synchrony Is Conditional on Mobility Patterns Vachuska, Karl Behav Sci (Basel) Article Recent research has attempted to document large-scale emotional contagion on online social networks. Despite emotional contagion being primarily driven by in-person mechanisms, less research has attempted to measure large-scale emotional contagion in in-person contexts. In this paper, I operationalize the temporal emotions associated with a particular city at particular points in time using sentiment analysis on Twitter data. Subsequently, I study how emotions converge between seven proximal cities in the state of Virginia, using two-way fixed effect models. I find that positive emotions tend to be synchronous between cities, but that effect is conditional on the level of contact between city residents at that period of time, as indicated by cell phone mobility data. I do not find any synchrony based on other types of emotions or general sentiment. I discourage drawing causal conclusions based on the presumed existence of several unmeasured sources of bias. MDPI 2022-10-25 /pmc/articles/PMC9687524/ /pubmed/36354387 http://dx.doi.org/10.3390/bs12110410 Text en © 2022 by the author. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Vachuska, Karl
Inter-City Emotional Synchrony Is Conditional on Mobility Patterns
title Inter-City Emotional Synchrony Is Conditional on Mobility Patterns
title_full Inter-City Emotional Synchrony Is Conditional on Mobility Patterns
title_fullStr Inter-City Emotional Synchrony Is Conditional on Mobility Patterns
title_full_unstemmed Inter-City Emotional Synchrony Is Conditional on Mobility Patterns
title_short Inter-City Emotional Synchrony Is Conditional on Mobility Patterns
title_sort inter-city emotional synchrony is conditional on mobility patterns
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9687524/
https://www.ncbi.nlm.nih.gov/pubmed/36354387
http://dx.doi.org/10.3390/bs12110410
work_keys_str_mv AT vachuskakarl intercityemotionalsynchronyisconditionalonmobilitypatterns