Bruns, A., Kasianenko, K., Suresh, V. P., Dehghan, E., & Vodden, L. (2025). Untangling the furball: A practice mapping approach to the analysis of multimodal interactions in social networks. Social Media + Society, 11, 20563051251331748. https://doi.org/10.1177/20563051251331748
Summary
This article introduces “practice mapping” as an analytical approach for studying social media interactions. Rather than relying on conventional node-and-edge network visualizations — which frequently collapse into illegible “hairball” or “furball” tangles as data scale grows — the authors propose representing users’ network actions as vector embeddings, then mapping the resulting commonalities and divergences in user practices within a unified analytical space. The central methodological advantage is the ability to integrate multiple distinct modes of interaction (e.g., replying, sharing, mentioning) into a single map, addressing a long-standing limitation of network analysis when applied to multimodal social media data. The paper is primarily a framework proposal rather than an empirical study.
Key Contributions
- Introduces practice mapping as a novel analytical approach for social media research.
- Provides a framework for incorporating multimodal interaction data into integrated visual analyses.
- Offers a methodological alternative to conventional, often illegible, network “furball” visualizations.
- Reframes the unit of analysis from network topology toward similarity in user practices.
Methods
- Presents the practice mapping framework conceptually rather than through a large empirical evaluation.
- Uses vector embeddings to represent the network actions and interactions of social media users.
- Maps commonalities and disjunctures across user practices in a shared analytical space, allowing multiple interaction modes to be combined into one representation.
Findings
- The abstract excerpt does not report specific empirical results; the contribution is chiefly methodological.
- The approach is argued to overcome the “hairball”/“furball” legibility problem of conventional network visualizations.
- Embedding-based representation is presented as capable of unifying multimodal interaction types that traditional network diagrams handle poorly.
Connections
This paper sits within the broader methodological conversation on how to analyze and represent complex online network structure, connecting to work by one of its own authors on network-based social media analysis Dehghan2026-sy. Its use of embeddings to reduce and compare structural behavior resonates with other computational-network approaches to detecting patterns and coordination in social media data, such as Minici2024-tf and Mannocci2025-ig.