Socio-Semantic Network Motifs Framework for Discourse Analysis
Paper presented at LAK '22
By Bodong Chen, Xinran Zhu, Hong Shui in publications
March 13, 2022
ABSTRACT
Effective collaborative discourse requires both cognitive and social engagement of students. To investigate complex socio-cognitive dynamics in collaborative discourse, this paper proposes to model collaborative discourse as a socio-semantic network (SSN) and then use network motifs – defined as recurring, significant subgraphs – to characterize the network and hence the discourse. To demonstrate the utility of our SSN motifs framework, we applied it to a sample dataset. While more work needs to be done, the SSN motifs framework shows promise as a novel, theoretically informed approach to discourse analysis.