CLCYSINov 30, 2023

Use of explicit replies as coordination mechanisms in online student debate

arXiv:2311.18466v1h-index: 12
Originality Synthesis-oriented
AI Analysis

This work addresses how linguistic coordination occurs in computer-mediated communication for researchers in computational linguistics and online education, but it appears incremental as it builds on existing frameworks.

The study tackled the problem of understanding coordination mechanisms in online student debates by analyzing explicit replies, using a non-parametric hierarchical topic model to identify community structures in vocabulary, and found that conversations vary in depth from general chatter to detailed sub-topics.

People in conversation entrain their linguistic behaviours through spontaneous alignment mechanisms [7] - both in face-to-face and computer-mediated communication (CMC) [8]. In CMC, one of the mechanisms through which linguistic entrainment happens is through explicit replies. Indeed, the use of explicit replies influences the structure of conversations, favouring the formation of reply-trees typically delineated by topic shifts [5]. The interpersonal coordination mechanisms realized by how actors address each other have been studied using a probabilistic framework proposed by David Gibson [2,3]. Other recent approaches use computational methods and information theory to quantify changes in text. We explore coordination mechanisms concerned with some of the roles utterances play in dialogues - specifically in explicit replies. We identify these roles by finding community structure in the conversation's vocabulary using a non-parametric, hierarchical topic model. Some conversations may always stay on the ground, remaining at the level of general introductory chatter. Some others may develop a specific sub-topic in significant depth and detail. Even others may jump between general chatter, out-of-topic remarks and people agreeing or disagreeing without further elaboration.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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