Prashant Khare, Ravi Shekhar, Mladen Karan, Stephen McQuistin, Colin Perkins, Ignacio Castro, Gareth Tyson, Patrick G. T. Healey, and Matthew Purver
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics,
July 2023.
DOI:10.18653/v1/2023.acl-short.8
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.
Download: khare2023tracing.pdf