| 书目名称 | Python for Graph and Network Analysis |
| 编辑 | Mohammed Zuhair Al-Taie,Seifedine Kadry |
| 视频video | |
| 概述 | Equips readers to practice network analysis using Python.Illustrates the complete process of network-level analysis.Treats both theoretical and practical aspects of detecting cohesive groups in networ |
| 丛书名称 | Advanced Information and Knowledge Processing |
| 图书封面 |  |
| 描述 | .This research monograph provides the means to learn the theory and practice of graph and network analysis using the Python programming language. The social network analysis techniques, included, will help readers to efficiently analyze social data from Twitter, Facebook, LiveJournal, GitHub and many others at three levels of depth: ego, group, and community. They will be able to analyse militant and revolutionary networks and candidate networks during elections. For instance, they will learn how the Ebola virus spread through communities. . .Practically, the book is suitable for courses on social network analysis in all disciplines that use social methodology. In the study of social networks, social network analysis makes an interesting interdisciplinary research area, where computer scientists and sociologists bring their competence to a level that will enable them to meet the challenges of this fast-developing field. Computer scientists have the knowledge to parse andprocess data while sociologists have the experience that is required for efficient data editing and interpretation. Social network analysis has successfully been applied in different fields such as health, cyber sec |
| 出版日期 | Book 2017 |
| 关键词 | Graph Theory; Information Diffusion; Social Network Analysis; Python; Group-level Analysis |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-53004-8 |
| isbn_softcover | 978-3-319-85037-5 |
| isbn_ebook | 978-3-319-53004-8Series ISSN 1610-3947 Series E-ISSN 2197-8441 |
| issn_series | 1610-3947 |
| copyright | Springer International Publishing AG 2017 |
发表于 2025-3-21 19:40:16
