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Commenter Behavior Characterization on YouTube Channels

Authors:
Shadi Shajari
Nitin Agarwal
Mustafa Alassad

Keywords: Social Network Analysis; YouTube; Commenter Network Analysis; Principal Component Analysis; Suspicious Behaviors;

Abstract:
YouTube is the second most visited website in the world and receives comments from millions of commenters daily. The comments section acts as a space for discussions among commenters, but it could also be a breeding ground for problematic behavior. In particular, the presence of suspicious commenters who engage in activities that deviate from the norms of constructive and respectful discourse can negatively impact the community and the quality of the online experience. This paper presents a social network analysis-based methodology for detecting commenter mobs on YouTube. These mobs of commenters collaborate to boost engagement on certain videos. The method provides a way to characterize channels based on the level of suspicious commenter behavior and detect coordination among channels. To evaluate our model, we analyzed 20 YouTube channels, 7,782 videos, 294,199 commenters, and 596,982 comments that propagated false views about the U.S. Military. The analysis concluded with evidence of commenter mob activities, possible coordinated suspicious behavior on the channels, and an explanation of the behavior of co-commenter communities.

Pages: 59 to 64

Copyright: Copyright (c) IARIA, 2023

Publication date: April 24, 2023

Published in: conference

ISSN: 2308-4375

ISBN: 978-1-68558-082-7

Location: Venice, Italy

Dates: from April 24, 2023 to April 28, 2023