Tracing Linguistic Markers of Influence in a Large Online Organisation

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 -the Internet Engineering Task Force (IETF), a collaborative organisation that develops technical standards for the Internet. Our analysis, based on lexical categories (LIWC) and BERT, shows that participants' levels of influence can be predicted from their email text, and identifies 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 1 .