Modelling Participation in Small Group Social Sequences with Markov Rewards Analysis

Gabriel Murray


Abstract
We explore a novel computational approach for analyzing member participation in small group social sequences. Using a complex state representation combining information about dialogue act types, sentiment expression, and participant roles, we explore which sequence states are associated with high levels of member participation. Using a Markov Rewards framework, we associate particular states with immediate positive and negative rewards, and employ a Value Iteration algorithm to calculate the expected value of all states. In our findings, we focus on discourse states belonging to team leaders and project managers which are either very likely or very unlikely to lead to participation from the rest of the group members.
Anthology ID:
W17-2910
Volume:
Proceedings of the Second Workshop on NLP and Computational Social Science
Month:
August
Year:
2017
Address:
Vancouver, Canada
Editors:
Dirk Hovy, Svitlana Volkova, David Bamman, David Jurgens, Brendan O’Connor, Oren Tsur, A. Seza Doğruöz
Venue:
NLP+CSS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
68–72
Language:
URL:
https://aclanthology.org/W17-2910
DOI:
10.18653/v1/W17-2910
Bibkey:
Cite (ACL):
Gabriel Murray. 2017. Modelling Participation in Small Group Social Sequences with Markov Rewards Analysis. In Proceedings of the Second Workshop on NLP and Computational Social Science, pages 68–72, Vancouver, Canada. Association for Computational Linguistics.
Cite (Informal):
Modelling Participation in Small Group Social Sequences with Markov Rewards Analysis (Murray, NLP+CSS 2017)
Copy Citation:
PDF:
https://aclanthology.org/W17-2910.pdf