Individuals use online social media platforms for social interaction and to create, consume and share creative content. Within large platforms, individuals’ interaction with content and the congregation of individuals sharing similar interests might have a dual relationship, leading to the emergence of focused content niches of specific individuals and types of content. These niches are smaller-scale social settings that may facilitate and structure interpersonal social interaction. This study introduces a novel two-step analytical framework to explore the influence of content niche affiliation on interaction patterns. In the first step, we employ Stochastic Block Models (SBMs) to analyze a two-mode network comprising content pieces and user-generated keywords assigned to them. This analysis uncovers distinct content niches where users can engage with one another. In the second step, We integrate these identified niches as independent variables within a Dynamic Network Actor Model (DyNAM) to investigate whether time-stamped user interaction dynamics are associated with these content niches. We illustrate the framework's applicability through a case study of an online community catering to aspiring and professional designers, revealing the relationship between content niche affiliation and social interactions.
Uzaheta, A., Amati, V., Stadtfeld, C. (2025). Modeling the duality of content niches and user interactions on online social media platforms. SOCIAL NETWORKS, 83(October 2025), 152-172 [10.1016/j.socnet.2025.05.001].
Modeling the duality of content niches and user interactions on online social media platforms
Amati V.;
2025
Abstract
Individuals use online social media platforms for social interaction and to create, consume and share creative content. Within large platforms, individuals’ interaction with content and the congregation of individuals sharing similar interests might have a dual relationship, leading to the emergence of focused content niches of specific individuals and types of content. These niches are smaller-scale social settings that may facilitate and structure interpersonal social interaction. This study introduces a novel two-step analytical framework to explore the influence of content niche affiliation on interaction patterns. In the first step, we employ Stochastic Block Models (SBMs) to analyze a two-mode network comprising content pieces and user-generated keywords assigned to them. This analysis uncovers distinct content niches where users can engage with one another. In the second step, We integrate these identified niches as independent variables within a Dynamic Network Actor Model (DyNAM) to investigate whether time-stamped user interaction dynamics are associated with these content niches. We illustrate the framework's applicability through a case study of an online community catering to aspiring and professional designers, revealing the relationship between content niche affiliation and social interactions.| File | Dimensione | Formato | |
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Uzaheta et al-2025-Social Networks-VoR.pdf
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