Tracing linguistic markers of influence in a large online organisation

Prashant Khare; Ravi Shekhar; Vanja Mladen Karan; Stephen McQuistin; Colin Perkins; Ignacio Castro; Gareth Tyson; Patrick G. T. Healey; Matthew Purver

doi:10.18653/v1/2023.acl-short.8

Tracing linguistic markers of influence in a large online organisation

Prashant Khare, Ravi Shekhar^*, Vanja Mladen Karan, Stephen McQuistin^*, Colin Perkins^*, Ignacio Castro, Gareth Tyson, Patrick G. T. Healey, Matthew Purver^*

^*Corresponding author for this work

School of Computer Science

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

Abstract

Social science and psycholinguistic research have shown that power and status affect how people use language in a range of domains. Here, we investigate a similar question in a large, distributed, consensus-driven community with little traditional power hierarchy – the Internet Engineering Task Force (IETF), a collaborative organisation that designs internet standards. Our analysis based on lexical categories (LIWC) and BERT, shows that participants’ levels of influence can be predicted from their email text, and identify key linguistic differences (e.g., certain LIWC categories, such as “WE” are positively correlated with high-influence). We also identify the differences in language use for the same person before and after becoming influential.

Original language	English
Title of host publication	Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
Editors	Anna Rogers, Jordan Boyd-Graber, Naoaki Okazaki
Place of Publication	Kerrville, TX
Publisher	Association for Computational Linguistics (ACL)
Pages	82-90
Number of pages	9
ISBN (Electronic)	9781959429715
DOIs	https://doi.org/10.18653/v1/2023.acl-short.8
Publication status	Published - 9 Jul 2023
Event	The 61st Annual Meeting of the Association for Computational Linguistics - Toronto, Canada Duration: 9 Jul 2023 → 14 Jul 2023 Conference number: 61 https://2023.aclweb.org

Publication series

Name	Proceedings of the annual meeting of the association for computational linguistics
Publisher	Association for Computational Linguistics
ISSN (Print)	0736-587X

Conference

Conference	The 61st Annual Meeting of the Association for Computational Linguistics
Abbreviated title	ACL
Country/Territory	Canada
City	Toronto
Period	9/07/23 → 14/07/23
Internet address	https://2023.aclweb.org

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Khare, P., Shekhar, R., Karan, V. M., McQuistin, S., Perkins, C., Castro, I., Tyson, G., Healey, P. G. T., & Purver, M. (2023). Tracing linguistic markers of influence in a large online organisation. In A. Rogers, J. Boyd-Graber, & N. Okazaki (Eds.), Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) (pp. 82-90). (Proceedings of the annual meeting of the association for computational linguistics). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2023.acl-short.8

Khare, Prashant ; Shekhar, Ravi ; Karan, Vanja Mladen et al. / Tracing linguistic markers of influence in a large online organisation. Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). editor / Anna Rogers ; Jordan Boyd-Graber ; Naoaki Okazaki. Kerrville, TX : Association for Computational Linguistics (ACL), 2023. pp. 82-90 (Proceedings of the annual meeting of the association for computational linguistics).

@inproceedings{817a402dd27b4cf280a9b5658d108fed,

title = "Tracing linguistic markers of influence in a large online organisation",

abstract = "Social science and psycholinguistic research have shown that power and status affect how people use language in a range of domains. Here, we investigate a similar question in a large, distributed, consensus-driven community with little traditional power hierarchy – the Internet Engineering Task Force (IETF), a collaborative organisation that designs internet standards. Our analysis based on lexical categories (LIWC) and BERT, shows that participants{\textquoteright} levels of influence can be predicted from their email text, and identify key linguistic differences (e.g., certain LIWC categories, such as “WE” are positively correlated with high-influence). We also identify the differences in language use for the same person before and after becoming influential.",

author = "Prashant Khare and Ravi Shekhar and Karan, \{Vanja Mladen\} and Stephen McQuistin and Colin Perkins and Ignacio Castro and Gareth Tyson and Healey, \{Patrick G. T.\} and Matthew Purver",

note = "Funding: This work was supported by the UK EPSRC under grants EP/S033564/1 and EP/S036075/1 (Sodestream: Streamlining Social Decision Making for Enhanced Internet Standards). Purver was also supported by the Slovenian Research Agency via research core funding for the programme Knowledge Technologies (P2-0103).; The 61st Annual Meeting of the Association for Computational Linguistics, ACL ; Conference date: 09-07-2023 Through 14-07-2023",

year = "2023",

month = jul,

day = "9",

doi = "10.18653/v1/2023.acl-short.8",

language = "English",

series = "Proceedings of the annual meeting of the association for computational linguistics",

publisher = "Association for Computational Linguistics (ACL)",

pages = "82--90",

editor = "Anna Rogers and Jordan Boyd-Graber and Naoaki Okazaki",

booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)",

url = "https://2023.aclweb.org",

}

Khare, P, Shekhar, R, Karan, VM, McQuistin, S, Perkins, C, Castro, I, Tyson, G, Healey, PGT & Purver, M 2023, Tracing linguistic markers of influence in a large online organisation. in A Rogers, J Boyd-Graber & N Okazaki (eds), Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). Proceedings of the annual meeting of the association for computational linguistics, Association for Computational Linguistics (ACL), Kerrville, TX, pp. 82-90, The 61st Annual Meeting of the Association for Computational Linguistics, Toronto, Canada, 9/07/23. https://doi.org/10.18653/v1/2023.acl-short.8

Tracing linguistic markers of influence in a large online organisation. / Khare, Prashant; Shekhar, Ravi; Karan, Vanja Mladen et al.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). ed. / Anna Rogers; Jordan Boyd-Graber; Naoaki Okazaki. Kerrville, TX: Association for Computational Linguistics (ACL), 2023. p. 82-90 (Proceedings of the annual meeting of the association for computational linguistics).

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

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T1 - Tracing linguistic markers of influence in a large online organisation

AU - Khare, Prashant

AU - Shekhar, Ravi

AU - Karan, Vanja Mladen

AU - McQuistin, Stephen

AU - Perkins, Colin

AU - Castro, Ignacio

AU - Tyson, Gareth

AU - Healey, Patrick G. T.

AU - Purver, Matthew

N1 - Conference code: 61

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N2 - Social science and psycholinguistic research have shown that power and status affect how people use language in a range of domains. Here, we investigate a similar question in a large, distributed, consensus-driven community with little traditional power hierarchy – the Internet Engineering Task Force (IETF), a collaborative organisation that designs internet standards. Our analysis based on lexical categories (LIWC) and BERT, shows that participants’ levels of influence can be predicted from their email text, and identify key linguistic differences (e.g., certain LIWC categories, such as “WE” are positively correlated with high-influence). We also identify the differences in language use for the same person before and after becoming influential.

AB - Social science and psycholinguistic research have shown that power and status affect how people use language in a range of domains. Here, we investigate a similar question in a large, distributed, consensus-driven community with little traditional power hierarchy – the Internet Engineering Task Force (IETF), a collaborative organisation that designs internet standards. Our analysis based on lexical categories (LIWC) and BERT, shows that participants’ levels of influence can be predicted from their email text, and identify key linguistic differences (e.g., certain LIWC categories, such as “WE” are positively correlated with high-influence). We also identify the differences in language use for the same person before and after becoming influential.

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BT - Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

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Khare P, Shekhar R, Karan VM, McQuistin S, Perkins C, Castro I et al. Tracing linguistic markers of influence in a large online organisation. In Rogers A, Boyd-Graber J, Okazaki N, editors, Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). Kerrville, TX: Association for Computational Linguistics (ACL). 2023. p. 82-90. (Proceedings of the annual meeting of the association for computational linguistics). doi: 10.18653/v1/2023.acl-short.8

Tracing linguistic markers of influence in a large online organisation

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