A First Course in Network Science (Hardcover)
Filippo Menczer , Santo Fortunato , Clayton A. Davis
- 出版商: Cambridge
- 出版日期: 2020-02-06
- 售價: $1,460
- 貴賓價: 9.8 折 $1,431
- 語言: 英文
- 頁數: 300
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 1108471137
- ISBN-13: 9781108471138
-
相關分類:
Python、程式語言、Web-crawler 網路爬蟲
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相關主題
商品描述
Networks are everywhere: networks of friends, transportation networks and the Web. Neurons in our brains and proteins within our bodies form networks that determine our intelligence and survival. This modern, accessible textbook introduces the basics of network science for a wide range of job sectors from management to marketing, from biology to engineering, and from neuroscience to the social sciences. Students will develop important, practical skills and learn to write code for using networks in their areas of interest - even as they are just learning to program with Python. Extensive sets of tutorials and homework problems provide plenty of hands-on practice and longer programming tutorials online further enhance students' programming skills. This intuitive and direct approach makes the book ideal for a first course, aimed at a wide audience without a strong background in mathematics or computing but with a desire to learn the fundamentals and applications of network science.
商品描述(中文翻譯)
網絡無所不在:朋友的網絡、交通網絡和網際網路。我們大腦中的神經元和我們身體內的蛋白質形成網絡,決定了我們的智力和生存能力。這本現代、易於理解的教科書介紹了網絡科學的基礎知識,適用於各種工作領域,從管理到營銷,從生物學到工程學,從神經科學到社會科學。學生將學習重要的實用技能,並學習編寫代碼,以在自己感興趣的領域中使用網絡 - 即使他們剛開始學習使用Python編程。大量的教程和作業問題提供了豐富的實踐機會,線上的長篇編程教程進一步提升了學生的編程能力。這種直觀和直接的方法使得這本書非常適合初學者,面向廣大的讀者群體,無需具備強大的數學或計算機背景,但渴望學習網絡科學的基礎知識和應用。
作者簡介
Filippo Menczer is Professor of Informatics and Computing at Indiana University, Bloomington. He is an ACM Distinguished Scientist and board member of the Indiana University Network Science Institute. He serves in editorial roles for several leading journals including Network Science, EPJ Data Science, and PeerJ: Computer Science. His research focuses on network science, computational social science, and Web science, with a focus on countering social media manipulation. His work on the spread of misinformation has received worldwide news coverage.
Santo Fortunato is Director of the Network Science Institute and Professor of Informatics at Indiana University, Bloomington. His current research is focused on network science, specifically network community detection, computational social science, and the 'science of science'. He received the German Physical Society's Young Scientist Award for Sociophysics and Econophysics in 2011 for his important contributions to the physics of social systems. He is Founding Chair of the International Conference on Computational Social Science (IC2S2).
Clayton A. Davis is an Informatics Ph.D. candidate at Indiana University, Bloomington and he holds B.S. and M.A. degrees in Mathematics. His research is concerned with the development of big-data platforms for social media analytics, machine learning algorithms for combating online abuse, design of crowdsourcing platforms, and the role of social media in social movements. His work on social bot detection was featured in major news outlets worldwide. His Web tools, including Botometer, Kinsey Reporter, and the Observatory on Social Media, answer millions of queries from thousands of users weekly. He won the 2017 Informatics Associate Instructor Award for his role in the development of high-quality teaching material for network science courses.
作者簡介(中文翻譯)
Filippo Menczer是印第安納大學布魯明頓分校的資訊學和計算學教授。他是ACM杰出科學家和印第安納大學網絡科學研究所的董事會成員。他在多個領先期刊擔任編輯職務,包括《網絡科學》、《EPJ數據科學》和《PeerJ:計算機科學》。他的研究重點是網絡科學、計算社會科學和Web科學,尤其關注對抗社交媒體操縱。他關於假消息傳播的研究獲得了全球新聞報導。
Santo Fortunato是印第安納大學布魯明頓分校的網絡科學研究所所長和資訊學教授。他目前的研究重點是網絡科學,特別是網絡社群檢測、計算社會科學和“科學的科學”。他於2011年獲得德國物理學會的社會物理學和經濟物理學青年科學家獎,以表彰他對社會系統物理學的重要貢獻。他是國際計算社會科學研討會(IC2S2)的創始主席。
Clayton A. Davis是印第安納大學布魯明頓分校的資訊學博士候選人,擁有數學學士和碩士學位。他的研究涉及開發用於社交媒體分析的大數據平台,應對線上虐待的機器學習算法,設計群眾外包平台以及社交媒體在社會運動中的作用。他關於社交機器人檢測的工作在全球主要新聞媒體中得到了報導。他的Web工具,包括Botometer、Kinsey Reporter和社交媒體觀察站,每週回答數百萬個用戶的數千個查詢。他因在網絡科學課程的高質量教材開發中的貢獻而獲得2017年資訊學副教學獎。
目錄大綱
Preface; Introduction
1. Network elements
2. Small worlds
3. Hubs
4. Directions and weights
5. Network models
6. Communities
7. Dynamics; Appendix
A. Python tutorial; Appendix
B. NetLogo models; Bibliography
目錄大綱(中文翻譯)
前言;引言
1. 網絡元素
2. 小世界
3. 中心節點
4. 方向和權重
5. 網絡模型
6. 社群
7. 動態;附錄
A. Python教程;附錄
B. NetLogo模型;參考文獻