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September 17, 2025Big Data and Cognitive Computing2 citationsOpen Access

Characterizing User Archetypes and Discussions on Social Hypernetworks

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AFAndrea FaillaSCSalvatore CitraroGRGiulio Rossetti

Key Points

  • Significant interactions on Scored.co involve an average of five participants, revealing complexity in online discussions.
  • The framework integrates various node features like user activity and toxicity to define distinct user archetypes.
  • Eight archetypes were identified, with one group exceeding 15,000 users, illustrating diverse roles in the network.
  • The analysis of over 4.4 million posts indicates stable yet dense interaction patterns among users, suggesting deep community ties.

Abstract

In recent years, the proliferation of social platforms has drastically transformed how individuals interact, organize, and share information. In this scenario, there has been an unprecedented increase in the scale and complexity of interactions and, at the same time, little to no research about certain fringe social platforms. In this paper, we present a multi-dimensional framework for characterizing nodes and hyperedges in social hypernetworks, with a focus on the understudied alt-right platform Scored.co. Our approach integrates the possibility of studying higher-order interactions, thanks to the hypernetwork representation, and various node features such as user activity, sentiment, and toxicity, with the aim of defining distinct user archetypes and understanding their roles within the network. Utilizing a comprehensive dataset from Scored.co, consisting of more than 4.4 M posts and 36.9 M comments, we analyze the dynamics of these archetypes over time and explore their interactions and influence within the community. We identify eight archetypes, with the largest group comprising over 15,000 users, and observe that 44% of interactions involve at least five participants, highlighting the importance of higher-order modeling. Furthermore, we find significant archetype transitions and stable yet locally dense interaction patterns, with users exposed to roughly 1000 unique peers on average. The framework’s versatility allows for detailed analysis of both individual user behaviors and broader social structures. Our findings highlight the importance of higher-order interactions and node features in understanding social dynamics, and offer new insights into the roles and behaviors that emerge in complex online environments.

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Cite This Study

Failla et al. (2025) studied this question.

synapsesocial.com/papers/68d45e4431b076d99fa5e287https://doi.org/10.3390/bdcc9090236
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