Comment Section Personalization: Algorithmic, Interface, and Interaction Design

Yixue Wang


Abstract
Comment sections allow users to share their personal experiences, discuss and form different opinions, and build communities out of organic conversations. However, many comment sections present chronological ranking to all users. In this paper, I discuss personalization approaches in comment sections based on different objectives for newsrooms and researchers to consider. I propose algorithmic and interface designs when personalizing the presentation of comments based on different objectives including relevance, diversity, and education/background information. I further explain how transparency, user control, and comment type diversity could help users most benefit from the personalized interacting experience.
Anthology ID:
2021.hackashop-1.12
Volume:
Proceedings of the EACL Hackashop on News Media Content Analysis and Automated Report Generation
Month:
April
Year:
2021
Address:
Online
Editors:
Hannu Toivonen, Michele Boggia
Venue:
Hackashop
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
84–88
Language:
URL:
https://aclanthology.org/2021.hackashop-1.12
DOI:
Bibkey:
Cite (ACL):
Yixue Wang. 2021. Comment Section Personalization: Algorithmic, Interface, and Interaction Design. In Proceedings of the EACL Hackashop on News Media Content Analysis and Automated Report Generation, pages 84–88, Online. Association for Computational Linguistics.
Cite (Informal):
Comment Section Personalization: Algorithmic, Interface, and Interaction Design (Wang, Hackashop 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.hackashop-1.12.pdf