‘Running to the Comments’: Examining the Cross-Platform Elasticity of Comment-to-Like Ratios Across Instagram and TikTok
Year: 2026
Type: article
Abstract: Audience engagement in the form of comments and likes has long been known to influence the visibility of content creators, but little has been discussed in the ways that these interaction ecologies diverge between platforms. Using poetry posts surfaced from Instagram and TikTok’s search results as a case study, this paper utilises a regression model to compare the elasticity of growth for comment-to-like ratios between platforms. Results demonstrate that for low-engagement posts, Instagram’s ratios are higher, but those on TikTok scale at a much faster rate once posts gain more traction. The paper discusses comment strategies that content creators may use to leverage this information in an economy where attention grows scarce and social proof is increasingly more valuable.
Source: Journalism and Media
Author: JuEunhae Knox
Institution: University of Stirling
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,207
OpenAlex ID: W7224884158