SimSpark: Interactive Simulation of Social Media Behaviors
Ziyue Lin, Yi Shan, Lin Gao, Xinghua Jia, Siming Chen

TL;DR
SimSpark is an interactive social media simulation platform that enables customizable, believable agent behaviors and real-time analysis, aiding researchers in understanding and testing social media dynamics without relying on real data.
Contribution
This paper introduces SimSpark, a flexible simulation system with visual interfaces and large language model-based behavior generation for social media research.
Findings
Effective in generating believable social media behaviors
Supports real-time parameter adjustments and analysis
Validated through case studies and expert feedback
Abstract
Understanding user behaviors on social media has garnered significant scholarly attention, enhancing our comprehension of how virtual platforms impact society and empowering decision-makers. Simulating social media behaviors provides a robust tool for capturing the patterns of social media behaviors, testing hypotheses, and predicting the effects of various interventions, ultimately contributing to a deeper understanding of social media environments. Moreover, it can overcome difficulties associated with utilizing real data for analysis, such as data accessibility issues, ethical concerns, and the complexity of processing large and heterogeneous datasets. However, researchers and stakeholders need more flexible platforms to investigate different user behaviors by simulating different scenarios and characters, which is not possible yet. Therefore, this paper introduces SimSpark, an…
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