Abstract
A modern interdisciplinary analysis of social networks implies detecting and investigating relevant socio-psychological linguistic markers that carry insight on the nature and characteristics of the social discourse. Associating markers to specific words is a further important step, allowing for an even richer interpretation. By taking as a working example the social discourse in Twitter, we propose a scalable method called PageRank-like marker projection (PLMP) following a rationale inspired by PageRank to fully exploit the interdependencies in a semantic network, so as to meaningfully project markers from a social discourse level (tweets) to its semantic elements (words). The effectiveness of PLMP is shown with an application example on calls to online collective action.
Published Version
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