YSocial: An artificial intelligence powered social media virtual twin

This paper introduces YSocial, a new-generation virtual twin designed to replicate an online social media platform. Digital and virtual twins are virtual replicas of physical systems that allow for advanced analyses, control, experimentation, and scenario simulations. In the case of social media, a virtual twin such as YSocial provides a powerful tool for researchers to simulate and understand complex online interactions. YSocial leverages state-of-the-art large language models (LLMs) to replicate sophisticated agent behaviors, enabling accurate simulations of user interactions, content dissemination, and network dynamics. By integrating these aspects, YSocial offers valuable insights into user engagement, information spread, and the impact of platform policies. Moreover, integrating LLMs allows YSocial to generate nuanced textual content and predict user responses, facilitating the study of emergent phenomena in online environments. To better characterize YSocial, we describe the rationale behind its implementation, provide examples of the analyses that can be performed on the data it generates, and discuss its relevance for multidisciplinary research.

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Publication Details

Journal
Big Data & Society
Published
2026-07-18
DOI
https://doi.org/10.1177/20539517261431576
Primary Topic
Complex Network Analysis Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

YSocial: An artificial intelligence powered social media virtual twin

Giulio Rossetti, Salvatore Citraro, Rémy Cazabet, Massimo Stella et al.
Big Data & Society
Complex Network Analysis Techniques
article

YSocial: An artificial intelligence powered social media virtual twin

Giulio Rossetti, Salvatore Citraro, Rémy Cazabet, Massimo Stella, Katherine Abramski, Virginia Morini, Andrea Failla, Erica Cau, Valentina Pansanella
article en

Abstract

This paper introduces YSocial, a new-generation virtual twin designed to replicate an online social media platform. Digital and virtual twins are virtual replicas of physical systems that allow for advanced analyses, control, experimentation, and scenario simulations. In the case of social media, a virtual twin such as YSocial provides a powerful tool for researchers to simulate and understand complex online interactions. YSocial leverages state-of-the-art large language models (LLMs) to replicate sophisticated agent behaviors, enabling accurate simulations of user interactions, content dissemination, and network dynamics. By integrating these aspects, YSocial offers valuable insights into user engagement, information spread, and the impact of platform policies. Moreover, integrating LLMs allows YSocial to generate nuanced textual content and predict user responses, facilitating the study of emergent phenomena in online environments. To better characterize YSocial, we describe the rationale behind its implementation, provide examples of the analyses that can be performed on the data it generates, and discuss its relevance for multidisciplinary research.

Big Data & SocietyVol. 13(3)
Université Claude Bernard Lyon 1 (FR), University of Pisa (IT), University of Trento (IT)
NextGenerationEU
Quality Education
Openalex Percentile: Top 8%
Complex Network Analysis Techniques
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YSocial: An artificial intelligence powered social media virtual twin — Giulio Rossetti, Salvatore Citraro, et al. · Big Data & Society (2026) | TGRS Research Map | TGRS