We study the perception of situational power in written dialogs in the context of organizational emails and contrast it to the power attributed by organizational hierarchy. We analyze various correlates of the perception of power in the dialog structure and language use by participants in the dialog. We also present an SVM-based machine learning system using dialog structure and lexical features to predict persons with situational power in a given communication thread.
In REF , we studied the notion of situational power in depth and presented a system to detect persons with situational power using dialog features.
Who's (Really) the Boss? Perception of Situational Power in Written Interactions
COLING
Computer Science