@inproceedings{2689439b7dff4e4197b4f87061cdaf68,
title = "Socio-Semantic Network Motifs Framework for Discourse Analysis",
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.",
keywords = "collaboration, discourse, networks, two-mode networks",
author = "Bodong Chen and Xinran Zhu and Hong Shui",
note = "Publisher Copyright: {\textcopyright} 2022 ACM.; 12th International Conference on Learning Analytics and Knowledge: Learning Analytics for Transition, Disruption and Social Change, LAK 2022 ; Conference date: 21-03-2022 Through 25-03-2022",
year = "2022",
month = mar,
day = "21",
doi = "10.1145/3506860.3506893",
language = "English (US)",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "500--506",
booktitle = "LAK 2022 - Conference Proceedings",
address = "United States",
}