講座題目：Prediction and Prevention of Disproportionally Influential Agents in Complex Networks

時(shí)間：2021年4月8日（周四）12:25– 13:25 博學(xué)樓925（線(xiàn)下）

主講人: Sandro Lera南方科技大學(xué)風(fēng)險(xiǎn)分析預(yù)測(cè)與管控研究院、信息系統(tǒng)與管理工程系雙聘助理教授、博士生導(dǎo)師。

主講人簡(jiǎn)介：

Sandro Lera南方科技大學(xué)風(fēng)險(xiǎn)分析預(yù)測(cè)與管控研究院、信息系統(tǒng)與管理工程系雙聘助理教授、博士生導(dǎo)師。他也是美國(guó)麻省理工學(xué)院訪(fǎng)問(wèn)學(xué)者，之前在美國(guó)麻省理工學(xué)院媒體實(shí)驗(yàn)室（MIT Media Lab）師從著名數(shù)據(jù)科學(xué)家Alex Pentland任博士后。研究方向主要為復(fù)雜系統(tǒng)、網(wǎng)絡(luò)科學(xué)、量化金融等。此外，Sandro Lera具有算法交易的行業(yè)背景，并為多家國(guó)際知名公司制定量化交易策略。文章的共同作者是麻省理工學(xué)院（MIT）的Alex Pentland教授和南方科技大學(xué)風(fēng)險(xiǎn)分析預(yù)測(cè)與管控研究院院長(zhǎng)Didier Sornette教授。

講座內(nèi)容簡(jiǎn)介：

We develop an early warning system and subsequent optimal intervention policy to avoid the formation of disproportional dominance (“winner takes all,” WTA) in growing complex networks. This is modeled as a system of interacting agents, whereby the rate at which an agent establishes connections to others is proportional to its already existing number of connections and its intrinsic fitness. We derive an exact four-dimensional phase diagram that separates the growing system into two regimes: one where the “fit get richer” and one where, eventually, the WTA. By calibrating the system’s parameters with maximum likelihood, its distance from the unfavorable WTA regime can be monitored in real time. This is demonstrated by combining the theory with big data in two applications: the social trading platform eToro and US supply-chain networks.

The eToro social trading platform where users mimic each other’s trades. If the system state is within or close to the WTA regime, we show how to efficiently control the system back into a more stable state along a geodesic path in the space of fitness distributions. We analyze (US) supply chain data in context of our model, and find that the common measure of penalizing the most dominant agents does not solve sustainably the problem of drastic inequity. Instead, interventions that first create a critical mass of high-fitness individuals followed by pushing the relatively low-fitness individuals upward is the best way to avoid swelling inequity and escalating fragility.

Our results call for a more wholistic approach, with important implications for the structure of regulatory matters such as antitrust policies, taxation law, subsidies, or development aid.