Communication Design Quarterly Jul 2021 Open Access

A machine learning algorithm for sorting online comments via topic modeling

Junzhe Zhu University of Illinois Urbana-Champaign ; Elizabeth Wickes University of Illinois Urbana-Champaign ; John R. Gallagher

Abstract

This article uses a machine learning algorithm to demonstrate a proof-of-concept case for moderating and managing online comments as a form of content moderation, which is an emerging area of interest for technical and professional communication (TPC) researchers. The algorithm sorts comments by topical similarity to a reference comment/article rather than display comments by linear time and popularity. This approach has the practical benefit of enabling TPC researchers to reconceptualize content display systems in dynamic ways.

Journal
Communication Design Quarterly
Published
2021-07-01
DOI
10.1145/3453460.3453462
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Topics
professional writing artificial intelligence
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Citation Context

Cited by in this index (3)

  1. Gupta et al. (2024)
    “Wayfinding” through the AI wilderness: Mapping rhetorics of ChatGPT prompt wri…
    Computers and Composition
  2. Thominet et al. (2024)
    Role Play: Conversational Roles as a Framework for Reflexive Practice in AI-Ass…
    Journal of Technical Writing and Communication
  3. Majdik et al. (2023)
    Building Better Machine Learning Models for Rhetorical Analyses: The Use of Rhe…
    Technical Communication Quarterly

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CrossRef global citation count: 8 View in citation network → Build reading path →

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