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The Twitter Social Mobility Index: Measuring Social Distancing Practices With Geolocated Tweets
BACKGROUND: Social distancing is an important component of the response to the COVID-19 pandemic. Minimizing social interactions and travel reduces the rate at which the infection spreads and “flattens the curve” so that the medical system is better equipped to treat infected individuals. However, i...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7717895/ https://www.ncbi.nlm.nih.gov/pubmed/33048823 http://dx.doi.org/10.2196/21499 |
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author | Xu, Paiheng Dredze, Mark Broniatowski, David A |
author_facet | Xu, Paiheng Dredze, Mark Broniatowski, David A |
author_sort | Xu, Paiheng |
collection | PubMed |
description | BACKGROUND: Social distancing is an important component of the response to the COVID-19 pandemic. Minimizing social interactions and travel reduces the rate at which the infection spreads and “flattens the curve” so that the medical system is better equipped to treat infected individuals. However, it remains unclear how the public will respond to these policies as the pandemic continues. OBJECTIVE: The aim of this study is to present the Twitter Social Mobility Index, a measure of social distancing and travel derived from Twitter data. We used public geolocated Twitter data to measure how much users travel in a given week. METHODS: We collected 469,669,925 tweets geotagged in the United States from January 1, 2019, to April 27, 2020. We analyzed the aggregated mobility variance of a total of 3,768,959 Twitter users at the city and state level from the start of the COVID-19 pandemic. RESULTS: We found a large reduction (61.83%) in travel in the United States after the implementation of social distancing policies. However, the variance by state was high, ranging from 38.54% to 76.80%. The eight states that had not issued statewide social distancing orders as of the start of April ranked poorly in terms of travel reduction: Arkansas (45), Iowa (37), Nebraska (35), North Dakota (22), South Carolina (38), South Dakota (46), Oklahoma (50), Utah (14), and Wyoming (53). We are presenting our findings on the internet and will continue to update our analysis during the pandemic. CONCLUSIONS: We observed larger travel reductions in states that were early adopters of social distancing policies and smaller changes in states without such policies. The results were also consistent with those based on other mobility data to a certain extent. Therefore, geolocated tweets are an effective way to track social distancing practices using a public resource, and this tracking may be useful as part of ongoing pandemic response planning. |
format | Online Article Text |
id | pubmed-7717895 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-77178952020-12-09 The Twitter Social Mobility Index: Measuring Social Distancing Practices With Geolocated Tweets Xu, Paiheng Dredze, Mark Broniatowski, David A J Med Internet Res Original Paper BACKGROUND: Social distancing is an important component of the response to the COVID-19 pandemic. Minimizing social interactions and travel reduces the rate at which the infection spreads and “flattens the curve” so that the medical system is better equipped to treat infected individuals. However, it remains unclear how the public will respond to these policies as the pandemic continues. OBJECTIVE: The aim of this study is to present the Twitter Social Mobility Index, a measure of social distancing and travel derived from Twitter data. We used public geolocated Twitter data to measure how much users travel in a given week. METHODS: We collected 469,669,925 tweets geotagged in the United States from January 1, 2019, to April 27, 2020. We analyzed the aggregated mobility variance of a total of 3,768,959 Twitter users at the city and state level from the start of the COVID-19 pandemic. RESULTS: We found a large reduction (61.83%) in travel in the United States after the implementation of social distancing policies. However, the variance by state was high, ranging from 38.54% to 76.80%. The eight states that had not issued statewide social distancing orders as of the start of April ranked poorly in terms of travel reduction: Arkansas (45), Iowa (37), Nebraska (35), North Dakota (22), South Carolina (38), South Dakota (46), Oklahoma (50), Utah (14), and Wyoming (53). We are presenting our findings on the internet and will continue to update our analysis during the pandemic. CONCLUSIONS: We observed larger travel reductions in states that were early adopters of social distancing policies and smaller changes in states without such policies. The results were also consistent with those based on other mobility data to a certain extent. Therefore, geolocated tweets are an effective way to track social distancing practices using a public resource, and this tracking may be useful as part of ongoing pandemic response planning. JMIR Publications 2020-12-03 /pmc/articles/PMC7717895/ /pubmed/33048823 http://dx.doi.org/10.2196/21499 Text en ©Paiheng Xu, Mark Dredze, David A Broniatowski. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 03.12.2020. 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 work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Xu, Paiheng Dredze, Mark Broniatowski, David A The Twitter Social Mobility Index: Measuring Social Distancing Practices With Geolocated Tweets |
title | The Twitter Social Mobility Index: Measuring Social Distancing Practices With Geolocated Tweets |
title_full | The Twitter Social Mobility Index: Measuring Social Distancing Practices With Geolocated Tweets |
title_fullStr | The Twitter Social Mobility Index: Measuring Social Distancing Practices With Geolocated Tweets |
title_full_unstemmed | The Twitter Social Mobility Index: Measuring Social Distancing Practices With Geolocated Tweets |
title_short | The Twitter Social Mobility Index: Measuring Social Distancing Practices With Geolocated Tweets |
title_sort | twitter social mobility index: measuring social distancing practices with geolocated tweets |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7717895/ https://www.ncbi.nlm.nih.gov/pubmed/33048823 http://dx.doi.org/10.2196/21499 |
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