Cursing in English on Twitter

Wenbo Wang; Lu Chen; Krishnaprasad Thirunarayan; Amit P. Sheth

doi:10.1145/2531602.2531734

Cursing in English on Twitter

Wenbo Wang, Lu Chen, Krishnaprasad Thirunarayan, Amit P. Sheth

Computer Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Cursing is not uncommon during conversations in the physical world: 0.5% to 0.7% of all the words we speak are curse words, given that 1% of all the words are first-person plural pronouns (e.g., we, us, our). On social media, people can instantly chat with friends without face-to-face interaction, usually in a more public fashion and broadly disseminated through highly connected social network. Will these distinctive features of social media lead to a change in people's cursing behavior? In this paper, we examine the characteristics of cursing activity on a popular social media platform - Twitter, involving the analysis of about 51 million tweets and about 14 million users. In particular, we explore a set of questions that have been recognized as crucial for understanding cursing in offline communications by prior studies, including the ubiquity, utility, and contextual dependencies of cursing.

Original language	American English
Title of host publication	CSCW '14
Subtitle of host publication	Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing
Publisher	Association for Computing Machinery
Pages	415-425
Number of pages	11
ISBN (Print)	9781450325400
DOIs	https://doi.org/10.1145/2531602.2531734
State	Published - Feb 15 2014
Event	17th ACM Conference on Computer Supported Cooperative Work and Social Computing - Baltimore, MD, United States Duration: Feb 15 2014 → Feb 19 2014 Conference number: 17

Conference

Conference	17th ACM Conference on Computer Supported Cooperative Work and Social Computing
Abbreviated title	CSCW 2014
Country/Territory	United States
City	Baltimore, MD
Period	2/15/14 → 2/19/14

ASJC Scopus Subject Areas

Software
Human-Computer Interaction
Computer Networks and Communications

Keywords

Cursing
Emotion
Gender Difference
Profanity
Social Media
Twitter

Disciplines

Bioinformatics
Communication
Communication Technology and New Media
Computer Sciences
Databases and Information Systems
Life Sciences
OS and Networks
Physical Sciences and Mathematics
Science and Technology Studies
Social and Behavioral Sciences

Access to Document

10.1145/2531602.2531734License: Unspecified

Cite this

Wang, W, Chen, L, Thirunarayan, K & Sheth, AP 2014, Cursing in English on Twitter. in CSCW '14: Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing. Association for Computing Machinery, pp. 415-425, 17th ACM Conference on Computer Supported Cooperative Work and Social Computing, Baltimore, MD, United States, 2/15/14. https://doi.org/10.1145/2531602.2531734

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title = "Cursing in English on Twitter",

abstract = " Cursing is not uncommon during conversations in the physical world: 0.5% to 0.7% of all the words we speak are curse words, given that 1% of all the words are first-person plural pronouns (e.g., we, us, our). On social media, people can instantly chat with friends without face-to-face interaction, usually in a more public fashion and broadly disseminated through highly connected social network. Will these distinctive features of social media lead to a change in people's cursing behavior? In this paper, we examine the characteristics of cursing activity on a popular social media platform - Twitter, involving the analysis of about 51 million tweets and about 14 million users. In particular, we explore a set of questions that have been recognized as crucial for understanding cursing in offline communications by prior studies, including the ubiquity, utility, and contextual dependencies of cursing.",

keywords = "Cursing, Emotion, Gender Difference, Profanity, Social Media, Twitter",

author = "Wenbo Wang and Lu Chen and Krishnaprasad Thirunarayan and Sheth, {Amit P.}",

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AU - Wang, Wenbo

AU - Chen, Lu

AU - Thirunarayan, Krishnaprasad

AU - Sheth, Amit P.

N1 - Conference code: 17

PY - 2014/2/15

Y1 - 2014/2/15

N2 - Cursing is not uncommon during conversations in the physical world: 0.5% to 0.7% of all the words we speak are curse words, given that 1% of all the words are first-person plural pronouns (e.g., we, us, our). On social media, people can instantly chat with friends without face-to-face interaction, usually in a more public fashion and broadly disseminated through highly connected social network. Will these distinctive features of social media lead to a change in people's cursing behavior? In this paper, we examine the characteristics of cursing activity on a popular social media platform - Twitter, involving the analysis of about 51 million tweets and about 14 million users. In particular, we explore a set of questions that have been recognized as crucial for understanding cursing in offline communications by prior studies, including the ubiquity, utility, and contextual dependencies of cursing.

AB - Cursing is not uncommon during conversations in the physical world: 0.5% to 0.7% of all the words we speak are curse words, given that 1% of all the words are first-person plural pronouns (e.g., we, us, our). On social media, people can instantly chat with friends without face-to-face interaction, usually in a more public fashion and broadly disseminated through highly connected social network. Will these distinctive features of social media lead to a change in people's cursing behavior? In this paper, we examine the characteristics of cursing activity on a popular social media platform - Twitter, involving the analysis of about 51 million tweets and about 14 million users. In particular, we explore a set of questions that have been recognized as crucial for understanding cursing in offline communications by prior studies, including the ubiquity, utility, and contextual dependencies of cursing.

KW - Cursing

KW - Emotion

KW - Gender Difference

KW - Profanity

KW - Social Media

KW - Twitter

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PB - Association for Computing Machinery

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Y2 - 15 February 2014 through 19 February 2014

ER -

Cursing in English on Twitter

Abstract

Conference

ASJC Scopus Subject Areas

Keywords

Disciplines

Access to Document

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