Elements of Network Science: Theory, Methods and Applications in Stata, R and Python
暫譯: 網路科學要素：理論、方法及在 Stata、R 和 Python 中的應用
Zinilli, Antonio
商品描述
This book provides readers with a comprehensive guide to designing rigorous and effective network science tools using the statistical software platforms Stata, R, and Python.
Network science offers a means to understand and analyze complex systems that involve various types of relationships. This text bridges the gap between theoretical understanding and practical application, making network science more accessible to a wide range of users. It presents the statistical models pertaining to individual network techniques, followed by empirical applications that use both built-in and user-written packages, and reveals the mathematical and statistical foundations of each model, along with demonstrations involving calculations and step-by-step code implementation. In addition, each chapter is complemented by a case study that illustrates one of the several techniques discussed.
The introductory chapter serves as a roadmap for readers, providing an initial understanding of network science and guidance on the required packages, the second chapter focuses on the main concepts related to network properties. The next two chapters present the primary definitions and concepts in network science and various classes of graphs observed in real contexts. The final chapter explores the main social network models, including the family of exponential random graph models. Each chapter includes real-world data applications from the social sciences, using at least one of the platforms Stata, R, and Python, providing a more comprehensive understanding of the availability of network science methods across different software platforms. The underlying computer code and data sets are available online.
The book will appeal to graduate students, researchers and data scientists, mainly from the social sciences, who seek theoretical and applied tools to implement network science techniques in their work.
商品描述(中文翻譯)
這本書為讀者提供了一個全面的指南，幫助設計嚴謹且有效的網絡科學工具，使用統計軟體平台 Stata、R 和 Python。
網絡科學提供了一種理解和分析涉及各種關係的複雜系統的方法。本書彌合了理論理解與實際應用之間的鴻溝，使網絡科學對廣泛的用戶更具可及性。它介紹了與個別網絡技術相關的統計模型，隨後是使用內建和用戶自編套件的實證應用，並揭示了每個模型的數學和統計基礎，還包括計算和逐步代碼實現的示範。此外，每一章都附有案例研究，說明所討論的幾種技術之一。
導言章節作為讀者的路線圖，提供了對網絡科學的初步理解以及所需套件的指導，第二章則專注於與網絡特性相關的主要概念。接下來的兩章介紹了網絡科學中的主要定義和概念，以及在實際情境中觀察到的各類圖形。最後一章探討了主要的社會網絡模型，包括指數隨機圖模型的家族。每一章都包含來自社會科學的實際數據應用，使用至少一個平台 Stata、R 和 Python，提供對不同軟體平台上網絡科學方法可用性的更全面理解。底層的計算機代碼和數據集可在線獲取。
這本書將吸引研究生、研究人員和數據科學家，主要來自社會科學領域，他們尋求理論和應用工具，以在工作中實施網絡科學技術。
作者簡介
Dr. Antonio Zinilli is Senior Researcher at the Research Institute on Sustainable Economic Growth at the National Research Council of Italy (CNR) in Rome. He holds a PhD in Applied Social Sciences (Curriculum Quantitative Methods) from the Sapienza University of Rome. He is the coordinator of the CNR School in "Data Science: tools and methods for analysing complex Science, Technology and Innovation (STI) systems". His research, based on an interdisciplinary approach, focuses on the Science of Science, complex network models, and computational social science. He has a particular interest in the analysis and the modeling of knowledge spreading processes as well as the dynamics of R&I processes. He teaches Network Analysis and Text Mining using Python/Stata and has developed the Datanet command in Stata for Network Analysis.
作者簡介(中文翻譯)
安東尼奧·齊尼利博士是義大利國家研究委員會（CNR）位於羅馬的可持續經濟增長研究所的高級研究員。他擁有羅馬薩賓納大學的應用社會科學博士學位（定量方法課程）。他是CNR學校「數據科學：分析複雜科學、技術與創新（STI）系統的工具與方法」的協調員。他的研究基於跨學科的方法，專注於科學的科學、複雜網絡模型和計算社會科學。他特別關注知識傳播過程的分析與建模，以及研究與創新（R&I）過程的動態。他教授使用Python/Stata的網絡分析和文本挖掘，並在Stata中開發了用於網絡分析的Datanet命令。
