Python For Graph And Network Analysis
DOWNLOAD
Download Python For Graph And Network Analysis PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Python For Graph And Network Analysis book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Python For Graph And Network Analysis
DOWNLOAD
Author : Mohammed Zuhair Al-Taie
language : en
Publisher: Springer
Release Date : 2017-03-20
Python For Graph And Network Analysis written by Mohammed Zuhair Al-Taie and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-20 with Computers categories.
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 and process 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 security, business, animal social networks, information retrieval, and communications.
Practical Social Network Analysis With Python
DOWNLOAD
Author : Krishna Raj P.M.
language : en
Publisher: Springer
Release Date : 2018-08-25
Practical Social Network Analysis With Python written by Krishna Raj P.M. and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-25 with Computers categories.
This book focuses on social network analysis from a computational perspective, introducing readers to the fundamental aspects of network theory by discussing the various metrics used to measure the social network. It covers different forms of graphs and their analysis using techniques like filtering, clustering and rule mining, as well as important theories like small world phenomenon. It also presents methods for identifying influential nodes in the network and information dissemination models. Further, it uses examples to explain the tools for visualising large-scale networks, and explores emerging topics like big data and deep learning in the context of social network analysis. With the Internet becoming part of our everyday lives, social networking tools are used as the primary means of communication. And as the volume and speed of such data is increasing rapidly, there is a need to apply computational techniques to interpret and understand it. Moreover, relationships in molecular structures, co-authors in scientific journals, and developers in a software community can also be understood better by visualising them as networks. This book brings together the theory and practice of social network analysis and includes mathematical concepts, computational techniques and examples from the real world to offer readers an overview of this domain.
Handbook Of Graphs And Networks In People Analytics
DOWNLOAD
Author : Keith McNulty
language : en
Publisher: CRC Press
Release Date : 2022-06-19
Handbook Of Graphs And Networks In People Analytics written by Keith McNulty and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-19 with Business & Economics categories.
Handbook of Graphs and Networks in People Analytics: With Examples in R and Python covers the theory and practical implementation of graph methods in R and Python for the analysis of people and organizational networks. Starting with an overview of the origins of graph theory and its current applications in the social sciences, the book proceeds to give in-depth technical instruction on how to construct and store graphs from data, how to visualize those graphs compellingly and how to convert common data structures into graph-friendly form. The book explores critical elements of network analysis in detail, including the measurement of distance and centrality, the detection of communities and cliques, and the analysis of assortativity and similarity. An extension chapter offers an introduction to graph database technologies. Real data sets from various research contexts are used for both instruction and for end of chapter practice exercises and a final chapter contains data sets and exercises ideal for larger personal or group projects of varying difficulty level. Key features: Immediately implementable code, with extensive and varied illustrations of graph variants and layouts. Examples and exercises across a variety of real-life contexts including business, politics, education, social media and crime investigation. Dedicated chapter on graph visualization methods. Practical walkthroughs of common methodological uses: finding influential actors in groups, discovering hidden community structures, facilitating diverse interaction in organizations, detecting political alignment, determining what influences connection and attachment. Various downloadable data sets for use both in class and individual learning projects. Final chapter dedicated to individual or group project examples.
Social Network Analysis For Startups
DOWNLOAD
Author : Maksim Tsvetovat
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2011-10-06
Social Network Analysis For Startups written by Maksim Tsvetovat and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-10-06 with Business & Economics categories.
Does your startup rely on social network analysis? This concise guide provides a statistical framework to help you identify social processes hidden among the tons of data now available. Social network analysis (SNA) is a discipline that predates Facebook and Twitter by 30 years. Through expert SNA researchers, you'll learn concepts and techniques for recognizing patterns in social media, political groups, companies, cultural trends, and interpersonal networks. You'll also learn how to use Python and other open source tools—such as NetworkX, NumPy, and Matplotlib—to gather, analyze, and visualize social data. This book is the perfect marriage between social network theory and practice, and a valuable source of insight and ideas. Discover how internal social networks affect a company’s ability to perform Follow terrorists and revolutionaries through the 1998 Khobar Towers bombing, the 9/11 attacks, and the Egyptian uprising Learn how a single special-interest group can control the outcome of a national election Examine relationships between companies through investment networks and shared boards of directors Delve into the anatomy of cultural fads and trends—offline phenomena often mediated by Twitter and Facebook
Graph Analysis And Visualization
DOWNLOAD
Author : Richard Brath
language : en
Publisher: John Wiley & Sons
Release Date : 2015-01-27
Graph Analysis And Visualization written by Richard Brath and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-01-27 with Computers categories.
Wring more out of the data with a scientific approach to analysis Graph Analysis and Visualization brings graph theory out of the lab and into the real world. Using sophisticated methods and tools that span analysis functions, this guide shows you how to exploit graph and network analytic techniques to enable the discovery of new business insights and opportunities. Published in full color, the book describes the process of creating powerful visualizations using a rich and engaging set of examples from sports, finance, marketing, security, social media, and more. You will find practical guidance toward pattern identification and using various data sources, including Big Data, plus clear instruction on the use of software and programming. The companion website offers data sets, full code examples in Python, and links to all the tools covered in the book. Science has already reaped the benefit of network and graph theory, which has powered breakthroughs in physics, economics, genetics, and more. This book brings those proven techniques into the world of business, finance, strategy, and design, helping extract more information from data and better communicate the results to decision-makers. Study graphical examples of networks using clear and insightful visualizations Analyze specifically-curated, easy-to-use data sets from various industries Learn the software tools and programming languages that extract insights from data Code examples using the popular Python programming language There is a tremendous body of scientific work on network and graph theory, but very little of it directly applies to analyst functions outside of the core sciences – until now. Written for those seeking empirically based, systematic analysis methods and powerful tools that apply outside the lab, Graph Analysis and Visualization is a thorough, authoritative resource.
Graph Algorithms
DOWNLOAD
Author : Mark Needham
language : en
Publisher: O'Reilly Media
Release Date : 2019-05-16
Graph Algorithms written by Mark Needham and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-16 with Computers categories.
Discover how graph algorithms can help you leverage the relationships within your data to develop more intelligent solutions and enhance your machine learning models. You’ll learn how graph analytics are uniquely suited to unfold complex structures and reveal difficult-to-find patterns lurking in your data. Whether you are trying to build dynamic network models or forecast real-world behavior, this book illustrates how graph algorithms deliver value—from finding vulnerabilities and bottlenecks to detecting communities and improving machine learning predictions. This practical book walks you through hands-on examples of how to use graph algorithms in Apache Spark and Neo4j—two of the most common choices for graph analytics. Also included: sample code and tips for over 20 practical graph algorithms that cover optimal pathfinding, importance through centrality, and community detection. Learn how graph analytics vary from conventional statistical analysis Understand how classic graph algorithms work, and how they are applied Get guidance on which algorithms to use for different types of questions Explore algorithm examples with working code and sample datasets from Spark and Neo4j See how connected feature extraction can increase machine learning accuracy and precision Walk through creating an ML workflow for link prediction combining Neo4j and Spark
Diffusion In Social Networks
DOWNLOAD
Author : Paulo Shakarian
language : en
Publisher: Springer
Release Date : 2015-09-16
Diffusion In Social Networks written by Paulo Shakarian and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-09-16 with Computers categories.
This book presents the leading models of social network diffusion that are used to demonstrate the spread of disease, ideas, and behavior. It introduces diffusion models from the fields of computer science (independent cascade and linear threshold), sociology (tipping models), physics (voter models), biology (evolutionary models), and epidemiology (SIR/SIS and related models). A variety of properties and problems related to these models are discussed including identifying seeds sets to initiate diffusion, game theoretic problems, predicting diffusion events, and more. The book explores numerous connections between social network diffusion research and artificial intelligence through topics such as agent-based modeling, logic programming, game theory, learning, and data mining. The book also surveys key empirical results in social network diffusion, and reviews the classic and cutting-edge research with a focus on open problems.
Data Analysis With Python
DOWNLOAD
Author : David Taieb
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-12-31
Data Analysis With Python written by David Taieb and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-31 with Computers categories.
Learn a modern approach to data analysis using Python to harness the power of programming and AI across your data. Detailed case studies bring this modern approach to life across visual data, social media, graph algorithms, and time series analysis. Key FeaturesBridge your data analysis with the power of programming, complex algorithms, and AIUse Python and its extensive libraries to power your way to new levels of data insightWork with AI algorithms, TensorFlow, graph algorithms, NLP, and financial time seriesExplore this modern approach across with key industry case studies and hands-on projectsBook Description Data Analysis with Python offers a modern approach to data analysis so that you can work with the latest and most powerful Python tools, AI techniques, and open source libraries. Industry expert David Taieb shows you how to bridge data science with the power of programming and algorithms in Python. You'll be working with complex algorithms, and cutting-edge AI in your data analysis. Learn how to analyze data with hands-on examples using Python-based tools and Jupyter Notebook. You'll find the right balance of theory and practice, with extensive code files that you can integrate right into your own data projects. Explore the power of this approach to data analysis by then working with it across key industry case studies. Four fascinating and full projects connect you to the most critical data analysis challenges you’re likely to meet in today. The first of these is an image recognition application with TensorFlow – embracing the importance today of AI in your data analysis. The second industry project analyses social media trends, exploring big data issues and AI approaches to natural language processing. The third case study is a financial portfolio analysis application that engages you with time series analysis - pivotal to many data science applications today. The fourth industry use case dives you into graph algorithms and the power of programming in modern data science. You'll wrap up with a thoughtful look at the future of data science and how it will harness the power of algorithms and artificial intelligence. What you will learnA new toolset that has been carefully crafted to meet for your data analysis challengesFull and detailed case studies of the toolset across several of today’s key industry contextsBecome super productive with a new toolset across Python and Jupyter NotebookLook into the future of data science and which directions to develop your skills nextWho this book is for This book is for developers wanting to bridge the gap between them and data scientists. Introducing PixieDust from its creator, the book is a great desk companion for the accomplished Data Scientist. Some fluency in data interpretation and visualization is assumed. It will be helpful to have some knowledge of Python, using Python libraries, and some proficiency in web development.
Graph Based Natural Language Processing And Information Retrieval
DOWNLOAD
Author : Rada Mihalcea
language : en
Publisher: Cambridge University Press
Release Date : 2011-04-11
Graph Based Natural Language Processing And Information Retrieval written by Rada Mihalcea and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-04-11 with Computers categories.
Graph theory and the fields of natural language processing and information retrieval are well-studied disciplines. Traditionally, these areas have been perceived as distinct, with different algorithms, different applications and different potential end-users. However, recent research has shown that these disciplines are intimately connected, with a large variety of natural language processing and information retrieval applications finding efficient solutions within graph-theoretical frameworks. This book extensively covers the use of graph-based algorithms for natural language processing and information retrieval. It brings together topics as diverse as lexical semantics, text summarization, text mining, ontology construction, text classification and information retrieval, which are connected by the common underlying theme of the use of graph-theoretical methods for text and information processing tasks. Readers will come away with a firm understanding of the major methods and applications in natural language processing and information retrieval that rely on graph-based representations and algorithms.