TY - JOUR
T1 - The public that engages invisibly
T2 - what visible engagement fails to capture in online political communication
AU - Chen, Yijing
AU - Kmetty, Zoltán
AU - Iñiguez, Gerardo
AU - Omodei, Elisa
N1 - Publisher Copyright:
© 2025 The Author(s). Published with license by Taylor & Francis Group, LLC.
PY - 2025/8/13
Y1 - 2025/8/13
N2 - Measurements of political polarization online have so far largely focused on visible traces accessible through platform APIs, neglecting invisible traces that are not recorded or otherwise unavailable to researchers, which can reveal key aspects of political engagement online. Our study addresses this gap by investigating the polarization measurement bias that arises when only visible engagement is analyzed, uncovering disparities at both the user and channel levels. Analyzing a combined dataset that links survey responses with YouTube digital traces through data donation from a sample of Hungarian Internet users (𝑁=758), we find that users who engage visibly through commenting are more politically polarized, and exhibit a greater level of selective exposure to content than users who engage invisibly through viewing. Moreover, ideologically heterogeneous channels are more likely to share viewers than subscribers or commenters. Thus, relying solely on public comment data may simplify, even overstate the segregation of political channels. Our results suggest that research using only visible engagement may overestimate the extent of polarization and the prevalence of echo chambers on YouTube. We highlight the benefits of using combined datasets to address measurement bias in online political communication, and contribute to the polarization literature by providing a fresh evaluation of potential biases in platform-focused research.
AB - Measurements of political polarization online have so far largely focused on visible traces accessible through platform APIs, neglecting invisible traces that are not recorded or otherwise unavailable to researchers, which can reveal key aspects of political engagement online. Our study addresses this gap by investigating the polarization measurement bias that arises when only visible engagement is analyzed, uncovering disparities at both the user and channel levels. Analyzing a combined dataset that links survey responses with YouTube digital traces through data donation from a sample of Hungarian Internet users (𝑁=758), we find that users who engage visibly through commenting are more politically polarized, and exhibit a greater level of selective exposure to content than users who engage invisibly through viewing. Moreover, ideologically heterogeneous channels are more likely to share viewers than subscribers or commenters. Thus, relying solely on public comment data may simplify, even overstate the segregation of political channels. Our results suggest that research using only visible engagement may overestimate the extent of polarization and the prevalence of echo chambers on YouTube. We highlight the benefits of using combined datasets to address measurement bias in online political communication, and contribute to the polarization literature by providing a fresh evaluation of potential biases in platform-focused research.
UR - https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=ceuapplication2024&SrcAuth=WosAPI&KeyUT=WOS:001549285200001&DestLinkType=FullRecord&DestApp=WOS_CPL
U2 - 10.1080/19312458.2025.2542725
DO - 10.1080/19312458.2025.2542725
M3 - Article
SN - 1931-2458
JO - Communication Methods and Measures
JF - Communication Methods and Measures
ER -