Tracing Linguistic Markers of Influence in a Large Online Organisation (2023.acl-short)
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Prashant Khare, Ravi Shekhar, Mladen Karan, Stephen McQuistin, Colin Perkins, Ignacio Castro, Gareth Tyson, Patrick Healey, Matthew Purver
| Challenge: | Social science and psycholinguistic research have shown that power and status affect how people use language in a range of domains. |
| Approach: | They propose to use lexical categories and BERT to predict levels of influence in an online community and identify key linguistic differences between people before and after becoming influential. |
| Outcome: | The results show that participants' levels of influence can be predicted from their email text, and identify key differences in language use for the same person before and after becoming influential. |
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