TikTok StitchGraph: Characterizing communication patterns on TikTok through a collection of interaction networks
Mads H{\o}genhaug, Marcus Friis, Morten Pedersen, Luca Rossi

TL;DR
This paper introduces TikTok StitchGraph, a collection of interaction networks based on stitches, revealing communication patterns and structural preferences in TikTok conversations, and compares these with Twitter reply networks.
Contribution
It constructs and analyzes TikTok stitch-based graphs, characterizing communication patterns and comparing them with Twitter reply networks, providing new insights into TikTok's conversation structures.
Findings
Preference for star and star-like structures in communication
Aversion to cyclic conversation patterns
Similarity between TikTok and Twitter conversation networks
Abstract
We present TikTok StitchGraph: a collection of 36 graphs based on TikTok stitches. With its rapid growth and widespread popularity, TikTok presents a compelling platform for study, yet given its video-first nature the network structure of the conversations that it hosts remains largely unexplored. Leveraging its recently released APIs, in combination with web scraping, we construct graphs detailing stitch relations from both a video- and user-centric perspective. Specifically, we focus on user multi-digraphs, with vertices representing users and edges representing directed stitch relations. From the user graphs, we characterize common communication patterns of the stitch using frequent subgraph mining, finding a preference for stars and star-like structures, an aversion towards cyclic structures, and directional disposition favoring in- and out-stars over mixed-direction structures.…
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