Paper: Predicting Power Relations between Participants in Written Dialog from a Single Thread

ACL ID P14-2056
Title Predicting Power Relations between Participants in Written Dialog from a Single Thread
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2014
Authors

We introduce the problem of predicting who has power over whom in pairs of peo- ple based on a single written dialog. We propose a new set of structural features. We build a supervised learning system to predict the direction of power; our new features significantly improve the results over using previously proposed features.