The Science of Influencers and Superspreaders: Using Networks and Artificial Intelligence to Understand Fake News, Pandemics, Markets, and the Brain
暫譯: 影響者與超傳播者的科學：利用網絡與人工智慧理解假新聞、疫情、市場與大腦
Makse, Hernán A., Zava, Marta
商品描述
This book explores the identification of influencers in complex networks, bridging theoretical approaches with practical applications across diverse fields. It examines interdisciplinary complex systems, including online social media, biological networks, brain networks, socioeconomic and financial systems, and ecosystems. The research presented aims to benefit scientists in relevant areas and inspire new scientific inquiries, potentially advancing the field of influencer identification.
In this context, 'influencer' serves as an umbrella term for essential, core, or central nodes within any complex network. The book investigates various manifestations of influencers, such as key figures in social media, critical nodes in genetic and brain networks, keystone species in ecosystems, systemically important banks in financial markets, and disease superspreaders. These diverse scenarios are approached by mapping the influencer identification problem to challenges in physics or computer science.
The book caters to readers at three distinct levels:
1. Those seeking mathematically rigorous theories of influencers will find Chapter 2 particularly valuable, as it delves into the mathematical foundations of influencer identification algorithms. Subsequent chapters explore the application of these theories across various disciplines.
2. Data scientists interested in implementing these algorithms in their research and practical work will find relevant information throughout the book.
3. Professionals in finance, marketing, politics, and social media, as well as readers curious about the intersection of big data, influencers, and AI, will gain insights into how these tools can enhance decision-making processes. These readers are encouraged to focus on the introduction and chapters most relevant to their fields, while briefly reviewing the more technical sections.
By offering this multi-layered approach, the book aims to provide a comprehensive understanding of influencer identification in complex networks, from theoretical foundations to real-world applications across various domains.
商品描述(中文翻譯)
這本書探討了在複雜網絡中識別影響者的問題，將理論方法與各個領域的實際應用相結合。它考察了跨學科的複雜系統，包括在線社交媒體、生物網絡、大腦網絡、社會經濟和金融系統以及生態系統。所呈現的研究旨在使相關領域的科學家受益，並激發新的科學探究，潛在地推進影響者識別的領域。
在這個背景下，「影響者」作為一個總稱，指的是任何複雜網絡中的重要、核心或中心節點。這本書調查了影響者的各種表現形式，例如社交媒體中的關鍵人物、基因和大腦網絡中的關鍵節點、生態系統中的關鍵物種、金融市場中的系統重要銀行，以及疾病的超級傳播者。這些多樣的情境通過將影響者識別問題映射到物理學或計算機科學中的挑戰來進行探討。
本書針對三個不同層次的讀者：
1. 尋求數學上嚴謹的影響者理論的讀者將會發現第二章特別有價值，因為它深入探討了影響者識別算法的數學基礎。隨後的章節則探討了這些理論在各個學科中的應用。
2. 對於希望在其研究和實際工作中實施這些算法的數據科學家，本書中提供了相關的信息。
3. 在金融、行銷、政治和社交媒體領域的專業人士，以及對大數據、影響者和人工智慧交集感興趣的讀者，將獲得有關這些工具如何增強決策過程的見解。這些讀者被鼓勵專注於與其領域最相關的介紹和章節，同時簡要回顧更技術性的部分。
通過提供這種多層次的方法，本書旨在從理論基礎到各個領域的實際應用，全面理解複雜網絡中的影響者識別。
作者簡介
Hernan Makse currently serves as Distinguished Professor of Physics at the City College of New York, wherein he is responsible for the Complex Networks and Data Science Lab at the Levich Institute. He is also Member Affiliate at Memorial Sloan Kettering Cancer Center and CEO of Kcore Analytics, an AI company in New York City. He holds a Ph.D. degree in Physics from Boston University, he is Fellow of the American Physical Society and Member of the Brazilian Academy of Science. His research focuses on the theoretical understanding of complex systems from a statistical physics viewpoint. He is working towards developing of new emergent laws for complex systems, ranging from brain networks to biological and social systems.
Marta Zava currently teaches and conducts her research at the Department of Finance in Bocconi University, Milan. Her PhD dissertation was nominated among the three best doctoral thesis in complex systems in France. She holds a PhD from Goethe University, Frankfurt am Main, Germany. Her research bridges the domains of venture capital, network science, financial markets and artificial intelligence. She regularly contributes to academic publications and books, presents at international conferences and engages in public outreach.
作者簡介(中文翻譯)
赫南·馬克斯（Hernan Makse）目前擔任紐約市立大學的傑出物理學教授，負責Levich研究所的複雜網絡與數據科學實驗室。他同時是紀念斯隆-凱特林癌症中心的會員附屬成員，以及位於紐約市的人工智慧公司Kcore Analytics的首席執行官。他擁有波士頓大學的物理學博士學位，是美國物理學會的會士，並且是巴西科學院的成員。他的研究專注於從統計物理的角度理解複雜系統的理論。他正在致力於為複雜系統開發新的新興法則，這些系統範圍從大腦網絡到生物和社會系統。
馬爾塔·扎瓦（Marta Zava）目前在米蘭的博科尼大學金融系教授並進行研究。她的博士論文被提名為法國三篇最佳複雜系統博士論文之一。她擁有德國法蘭克福歌德大學的博士學位。她的研究橋接了風險投資、網絡科學、金融市場和人工智慧等領域。她定期為學術出版物和書籍貢獻文章，參加國際會議並參與公共宣傳活動。
