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Aysajan Eziz

Publications and source records attributed to Aysajan Eziz.

2 recordsLinked to original sources

Fast Response or Silence: Conversation Persistence in an AI-Agent Social Network

Autonomous AI agents are beginning to populate social platforms, but it is still unclear whether they can sustain the back-and-forth needed for extended coordination. We study Moltbook, an AI-agent social network, using a first-week snapshot and introduce interaction half-life: how quickly a comment's chance of receiving a direct reply fades as the comment ages. Across tens of thousands of commented threads, Moltbook discussions are dominated by first-layer reactions rather than extended chains. Most comments never receive a direct reply, reciprocal back-and-forth is rare, and when replies do occur they arrive almost immediately -- typically within seconds -- implying persistence on the order of minutes rather than hours. Moltbook is often described as running on an approximately four-hour ``heartbeat'' check-in schedule; using aggregate spectral tests on the longest contiguous activity window, we do not detect a reliable four-hour rhythm in this snapshot, consistent with jittered or out-of-phase individual schedules. A contemporaneous Reddit baseline analyzed with the same estimators shows substantially deeper threads and much longer reply persistence. Overall, early agent social interaction on Moltbook fits a ``fast response or silence'' regime, suggesting that sustained multi-step coordination will likely require explicit memory, thread resurfacing, and re-entry scaffolds.

econ.EM↗

Layer-2 Adoption and Ethereum Mainnet Congestion: Regime-Aware Causal Evidence Across London, the Merge, and Dencun (2021-2024)

Do Ethereum's Layer-2 (L2) rollups actually decongest the Layer-1 (L1) mainnet once protocol upgrades and demand are held constant? Using a 1245-day daily panel from August 5, 2021 to December 31, 2024 that spans the London, Merge, and Dencun upgrades, we link Ethereum fee and congestion metrics to L2 user activity, macro-demand proxies, and targeted event indicators. We estimate a regime-aware error-correction model that treats posting-clean L2 user share as a continuous treatment. Over the pre-Dencun (London+Merge) window, a 10 percentage point increase in L2 adoption lowers median base fees by about 13% -- roughly 5 Gwei at pre-Dencun levels -- and deviations from the long-run relation decay with an 11-day half-life. Block utilization and a scarcity index show similar congestion relief. After Dencun, L2 adoption is already high and treatment support narrows, so blob-era estimates are statistically imprecise and we treat them as exploratory. The pre-Dencun window therefore delivers the first cross-regime causal estimate of how aggregate L2 adoption decongests Ethereum, together with a reusable template for monitoring rollup-centric scaling strategies.

econ.GN↗