The growing amplification of social media: measuring temporal and social contagion dynamics for over 150 languages on Twitter for 2009–2020

Abstract Working from a dataset of 118 billion messages running from the start of 2009 to the end of 2019, we identify and explore the relative daily use of over 150 languages on Twitter. We find that eight languages comprise 80% of all tweets, with English, Japanese, Spanish, Arabic, and Portuguese...

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Main Authors:	Thayer Alshaabi, David Rushing Dewhurst, Joshua R. Minot, Michael V. Arnold, Jane L. Adams, Christopher M. Danforth, Peter Sheridan Dodds
Format:	Article
Language:	English
Published:	SpringerOpen 2021-03-01
Series:	EPJ Data Science
Subjects:	NLP Sociolinguistics Social contagion Twitter Signal processing
Online Access:	https://doi.org/10.1140/epjds/s13688-021-00271-0

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spelling	doaj-c0404a8bda824056b772c44e7b0403012021-04-04T11:05:56ZengSpringerOpenEPJ Data Science2193-11272021-03-0110112810.1140/epjds/s13688-021-00271-0The growing amplification of social media: measuring temporal and social contagion dynamics for over 150 languages on Twitter for 2009–2020Thayer Alshaabi0David Rushing Dewhurst1Joshua R. Minot2Michael V. Arnold3Jane L. Adams4Christopher M. Danforth5Peter Sheridan Dodds6Vermont Complex Systems Center, University of VermontVermont Complex Systems Center, University of VermontVermont Complex Systems Center, University of VermontVermont Complex Systems Center, University of VermontVermont Complex Systems Center, University of VermontVermont Complex Systems Center, University of VermontVermont Complex Systems Center, University of VermontAbstract Working from a dataset of 118 billion messages running from the start of 2009 to the end of 2019, we identify and explore the relative daily use of over 150 languages on Twitter. We find that eight languages comprise 80% of all tweets, with English, Japanese, Spanish, Arabic, and Portuguese being the most dominant. To quantify social spreading in each language over time, we compute the ‘contagion ratio’: The balance of retweets to organic messages. We find that for the most common languages on Twitter there is a growing tendency, though not universal, to retweet rather than share new content. By the end of 2019, the contagion ratios for half of the top 30 languages, including English and Spanish, had reached above 1—the naive contagion threshold. In 2019, the top 5 languages with the highest average daily ratios were, in order, Thai (7.3), Hindi, Tamil, Urdu, and Catalan, while the bottom 5 were Russian, Swedish, Esperanto, Cebuano, and Finnish (0.26). Further, we show that over time, the contagion ratios for most common languages are growing more strongly than those of rare languages.https://doi.org/10.1140/epjds/s13688-021-00271-0NLPSociolinguisticsSocial contagionTwitterSignal processing
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Thayer Alshaabi David Rushing Dewhurst Joshua R. Minot Michael V. Arnold Jane L. Adams Christopher M. Danforth Peter Sheridan Dodds
spellingShingle	Thayer Alshaabi David Rushing Dewhurst Joshua R. Minot Michael V. Arnold Jane L. Adams Christopher M. Danforth Peter Sheridan Dodds The growing amplification of social media: measuring temporal and social contagion dynamics for over 150 languages on Twitter for 2009–2020 EPJ Data Science NLP Sociolinguistics Social contagion Twitter Signal processing
author_facet	Thayer Alshaabi David Rushing Dewhurst Joshua R. Minot Michael V. Arnold Jane L. Adams Christopher M. Danforth Peter Sheridan Dodds
author_sort	Thayer Alshaabi
title	The growing amplification of social media: measuring temporal and social contagion dynamics for over 150 languages on Twitter for 2009–2020
title_short	The growing amplification of social media: measuring temporal and social contagion dynamics for over 150 languages on Twitter for 2009–2020
title_full	The growing amplification of social media: measuring temporal and social contagion dynamics for over 150 languages on Twitter for 2009–2020
title_fullStr	The growing amplification of social media: measuring temporal and social contagion dynamics for over 150 languages on Twitter for 2009–2020
title_full_unstemmed	The growing amplification of social media: measuring temporal and social contagion dynamics for over 150 languages on Twitter for 2009–2020
title_sort	growing amplification of social media: measuring temporal and social contagion dynamics for over 150 languages on twitter for 2009–2020
publisher	SpringerOpen
series	EPJ Data Science
issn	2193-1127
publishDate	2021-03-01
description	Abstract Working from a dataset of 118 billion messages running from the start of 2009 to the end of 2019, we identify and explore the relative daily use of over 150 languages on Twitter. We find that eight languages comprise 80% of all tweets, with English, Japanese, Spanish, Arabic, and Portuguese being the most dominant. To quantify social spreading in each language over time, we compute the ‘contagion ratio’: The balance of retweets to organic messages. We find that for the most common languages on Twitter there is a growing tendency, though not universal, to retweet rather than share new content. By the end of 2019, the contagion ratios for half of the top 30 languages, including English and Spanish, had reached above 1—the naive contagion threshold. In 2019, the top 5 languages with the highest average daily ratios were, in order, Thai (7.3), Hindi, Tamil, Urdu, and Catalan, while the bottom 5 were Russian, Swedish, Esperanto, Cebuano, and Finnish (0.26). Further, we show that over time, the contagion ratios for most common languages are growing more strongly than those of rare languages.
topic	NLP Sociolinguistics Social contagion Twitter Signal processing
url	https://doi.org/10.1140/epjds/s13688-021-00271-0
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The growing amplification of social media: measuring temporal and social contagion dynamics for over 150 languages on Twitter for 2009–2020

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