Do we swear more with friends or with acquaintances? F#ck in social networks

• We make use of nearly 8 billion words of social media from Australia, US and UK. • We use algorithmic methods to predict the use of fuck in social networks. • Americans use fuck most frequently, Australians least but they are highly creative. • People swear more with acquaintances than with friends, but only in smaller networks. • People tend to use fuck infrequently in small networks of fewer than 15 people. We investigate the uses of fuck in digital social networks from social media, Twitter/X in this case. Social media outlets have so far been predominantly treated as massive text collections, but they can be effectively used to investigate the role of social networks in shaping human communication. We use user-generated texts from 5,660 social networks (with 435,345 users and 7.8 billion words) from three settings (UK, US, and Australia). With embedded network information, this massive dataset enables us to investigate how network properties, that of the size and the strength of the network, influence the use of offensive words in these three settings. Our findings show that Americans use fuck most frequently, while Australians least frequently but they are highly creative with spelling variants of the word. Contrary to prior studies, we observe that people on this social media application swear more with acquaintances than with friends, but only in smaller networks − in larger networks of >100 people, the differences level out. Overall, this study highlights the benefits of using social media data that can be enriched to allow access to the social networks that people interact in.

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Institutions

Publication Details

Journal
Lingua
Published
2025-03-31
DOI
https://doi.org/10.1016/j.lingua.2025.103931
Citations
1
Primary Topic
Swearing, Euphemism, Multilingualism
Type
article
Field-Weighted Citation Impact
3.86

Funders

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article

Do we swear more with friends or with acquaintances? F#ck in social networks

Paula Rautionaho, Mikko Laitinen, Masoud Fatemi, Mikko Halonen
1 citations
Lingua
Swearing, Euphemism, Multilingualism
3.86
article

Do we swear more with friends or with acquaintances? F#ck in social networks

Paula Rautionaho, Mikko Laitinen, Masoud Fatemi, Mikko Halonen
article en
1 citations

Abstract

• We make use of nearly 8 billion words of social media from Australia, US and UK. • We use algorithmic methods to predict the use of fuck in social networks. • Americans use fuck most frequently, Australians least but they are highly creative. • People swear more with acquaintances than with friends, but only in smaller networks. • People tend to use fuck infrequently in small networks of fewer than 15 people. We investigate the uses of fuck in digital social networks from social media, Twitter/X in this case. Social media outlets have so far been predominantly treated as massive text collections, but they can be effectively used to investigate the role of social networks in shaping human communication. We use user-generated texts from 5,660 social networks (with 435,345 users and 7.8 billion words) from three settings (UK, US, and Australia). With embedded network information, this massive dataset enables us to investigate how network properties, that of the size and the strength of the network, influence the use of offensive words in these three settings. Our findings show that Americans use fuck most frequently, while Australians least frequently but they are highly creative with spelling variants of the word. Contrary to prior studies, we observe that people on this social media application swear more with acquaintances than with friends, but only in smaller networks − in larger networks of >100 people, the differences level out. Overall, this study highlights the benefits of using social media data that can be enriched to allow access to the social networks that people interact in.

LinguaVol. 320
University of Eastern Finland (FI), Linnaeus University (SE)
European Commission, Academy of Finland
Reduced inequalities
Openalex Percentile: Top 10%
Swearing, Euphemism, Multilingualism
3.86
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