47 papers
This study analyzes socialbot activity in modern Japanese social media, revealing that their influence exceeds that observed during the 2016 U.S. presidential election and that human-retweeted socialbots are difficult to distinguish from genuine human accounts.
This paper proposes a correlation-based metric and a simple common-neighbor clustering algorithm to achieve exact, almost exact, and weak recovery of small, heterogeneously-sized communities in the planted partition model, overcoming the limitations of traditional methods in highly unbalanced settings.
This paper establishes a strict hierarchy where graph dynamical models are a special case of focal hypergraph models, which in turn are a subset of general hypergraph models, demonstrating that the choice between these formalisms should be determined by the specific nature of interactions (focal versus non-focal) rather than a preference for one framework.
This paper analyzes a decade-long dataset of 2 million YouTube videos to reveal that while affiliate marketing is widespread, disclosure compliance with FTC guidelines remains critically low, suggesting that platform-standardized features are essential for improving transparency and trust in the influencer economy.
This paper proposes a temporal framework based on multivariate Hawkes processes to disentangle intrinsic interaction tendencies from algorithmic feedback in evolving networks, introducing an instantaneous bias measure that effectively captures and characterizes the real-time reinforcement dynamics induced by link prediction models.
This paper proposes UrbanHuRo, a two-layer human-robot collaboration framework that jointly optimizes heterogeneous urban services like crowdsourced delivery and sensing through scalable order dispatch and deep reinforcement learning, achieving significant improvements in sensing coverage, courier income, and order timeliness.
This paper introduces MoltBook, a large-scale environment for observing autonomous LLM agents, and reports that while these agents exhibit emergent structural role specialization and power-law information cascades, their cooperative task resolution remains nascent and significantly less effective than single-agent performance.