Practical Social Network Analysis With Python

Author : Krishna Raj P.M.,Ankith Mohan,K.G. Srinivasa
Publisher : Springer
Page : 329 pages
File Size : 46,9 Mb
Release : 2018-08-25
Category : Computers
ISBN : 9783319967462

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Practical Social Network Analysis with Python by Krishna Raj P.M.,Ankith Mohan,K.G. Srinivasa Pdf

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.

Author : Mohammed Zuhair Al-Taie,Seifedine Kadry
Publisher : Springer
Page : 203 pages
File Size : 44,5 Mb
Release : 2017-03-20
Category : Computers
ISBN : 9783319530048

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Python for Graph and Network Analysis by Mohammed Zuhair Al-Taie,Seifedine Kadry Pdf

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.

Author : David Knickerbocker
Publisher : Packt Publishing Ltd
Page : 414 pages
File Size : 52,7 Mb
Release : 2023-02-28
Category : Computers
ISBN : 9781801075213

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Network Science with Python by David Knickerbocker Pdf

Discover the use of graph networks to develop a new approach to data science using theoretical and practical methods with this expert guide using Python, printed in color Key FeaturesCreate networks using data points and informationLearn to visualize and analyze networks to better understand communitiesExplore the use of network data in both - supervised and unsupervised machine learning projectsPurchase of the print or Kindle book includes a free PDF eBookBook Description Network analysis is often taught with tiny or toy data sets, leaving you with a limited scope of learning and practical usage. Network Science with Python helps you extract relevant data, draw conclusions and build networks using industry-standard – practical data sets. You'll begin by learning the basics of natural language processing, network science, and social network analysis, then move on to programmatically building and analyzing networks. You'll get a hands-on understanding of the data source, data extraction, interaction with it, and drawing insights from it. This is a hands-on book with theory grounding, specific technical, and mathematical details for future reference. As you progress, you'll learn to construct and clean networks, conduct network analysis, egocentric network analysis, community detection, and use network data with machine learning. You'll also explore network analysis concepts, from basics to an advanced level. By the end of the book, you'll be able to identify network data and use it to extract unconventional insights to comprehend the complex world around you. What you will learnExplore NLP, network science, and social network analysisApply the tech stack used for NLP, network science, and analysisExtract insights from NLP and network dataGenerate personalized NLP and network projectsAuthenticate and scrape tweets, connections, the web, and data streamsDiscover the use of network data in machine learning projectsWho this book is for Network Science with Python demonstrates how programming and social science can be combined to find new insights. Data scientists, NLP engineers, software engineers, social scientists, and data science students will find this book useful. An intermediate level of Python programming is a prerequisite. Readers from both – social science and programming backgrounds will find a new perspective and add a feather to their hat.

Author : Dmitry Zinoviev
Publisher : Pragmatic Bookshelf
Page : 343 pages
File Size : 53,6 Mb
Release : 2018-01-19
Category : Computers
ISBN : 9781680505405

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Complex Network Analysis in Python by Dmitry Zinoviev Pdf

Construct, analyze, and visualize networks with networkx, a Python language module. Network analysis is a powerful tool you can apply to a multitude of datasets and situations. Discover how to work with all kinds of networks, including social, product, temporal, spatial, and semantic networks. Convert almost any real-world data into a complex network--such as recommendations on co-using cosmetic products, muddy hedge fund connections, and online friendships. Analyze and visualize the network, and make business decisions based on your analysis. If you're a curious Python programmer, a data scientist, or a CNA specialist interested in mechanizing mundane tasks, you'll increase your productivity exponentially. Complex network analysis used to be done by hand or with non-programmable network analysis tools, but not anymore! You can now automate and program these tasks in Python. Complex networks are collections of connected items, words, concepts, or people. By exploring their structure and individual elements, we can learn about their meaning, evolution, and resilience. Starting with simple networks, convert real-life and synthetic network graphs into networkx data structures. Look at more sophisticated networks and learn more powerful machinery to handle centrality calculation, blockmodeling, and clique and community detection. Get familiar with presentation-quality network visualization tools, both programmable and interactive--such as Gephi, a CNA explorer. Adapt the patterns from the case studies to your problems. Explore big networks with NetworKit, a high-performance networkx substitute. Each part in the book gives you an overview of a class of networks, includes a practical study of networkx functions and techniques, and concludes with case studies from various fields, including social networking, anthropology, marketing, and sports analytics. Combine your CNA and Python programming skills to become a better network analyst, a more accomplished data scientist, and a more versatile programmer. What You Need: You will need a Python 3.x installation with the following additional modules: Pandas (>=0.18), NumPy (>=1.10), matplotlib (>=1.5), networkx (>=1.11), python-louvain (>=0.5), NetworKit (>=3.6), and generalizesimilarity. We recommend using the Anaconda distribution that comes with all these modules, except for python-louvain, NetworKit, and generalizedsimilarity, and works on all major modern operating systems.

Author : Maksim Tsvetovat,Alexander Kouznetsov
Publisher : "O'Reilly Media, Inc."
Page : 192 pages
File Size : 53,8 Mb
Release : 2011-09-27
Category : Electronic
ISBN : 9781449317621

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Social Network Analysis for Startups by Maksim Tsvetovat,Alexander Kouznetsov Pdf

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

Author : Mohammad Gouse Galety,Chiai Al Atroshi,Buni Balabantaray,Sachi Nandan Mohanty
Publisher : John Wiley & Sons
Page : 260 pages
File Size : 40,9 Mb
Release : 2022-05-24
Category : Technology & Engineering
ISBN : 9781119836230

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Social Network Analysis by Mohammad Gouse Galety,Chiai Al Atroshi,Buni Balabantaray,Sachi Nandan Mohanty Pdf

SOCIAL NETWORK ANALYSIS As social media dominates our lives in increasing intensity, the need for developers to understand the theory and applications is ongoing as well. This book serves that purpose. Social network analysis is the solicitation of network science on social networks, and social occurrences are denoted and premeditated by data on coinciding pairs as the entities of opinion. The book features: Social network analysis from a computational perspective using python to show the significance of fundamental facets of network theory and the various metrics used to measure the social network. An understanding of network analysis and motivations to model phenomena as networks. Real-world networks established with human-related data frequently display social properties, i.e., patterns in the graph from which human behavioral patterns can be analyzed and extracted. Exemplifies information cascades that spread through an underlying social network to achieve widespread adoption. Network analysis that offers an appreciation method to health systems and services to illustrate, diagnose, and analyze networks in health systems. The social web has developed a significant social and interactive data source that pays exceptional attention to social science and humanities research. The benefits of artificial intelligence enable social media platforms to meet an increasing number of users and yield the biggest marketplace, thus helping social networking analysis distribute better customer understanding and aiding marketers to target the right customers. Audience The book will interest computer scientists, AI researchers, IT and software engineers, mathematicians.

Author : Dmitry Zinoviev
Publisher : Unknown
Page : 128 pages
File Size : 55,6 Mb
Release : 2018
Category : Electronic
ISBN : 1680505394

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Complex Network Analysis in Python by Dmitry Zinoviev Pdf

Author : Keith McNulty
Publisher : CRC Press
Page : 269 pages
File Size : 41,7 Mb
Release : 2022-06-19
Category : Business & Economics
ISBN : 9781000597233

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Handbook of Graphs and Networks in People Analytics by Keith McNulty Pdf

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.

Author : Stephen P Borgatti,Martin G Everett,Jeffrey C Johnson
Publisher : SAGE
Page : 371 pages
File Size : 44,9 Mb
Release : 2013-05-14
Category : Social Science
ISBN : 9781446290569

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Analyzing Social Networks by Stephen P Borgatti,Martin G Everett,Jeffrey C Johnson Pdf

Written by a stellar team of experts, Analyzing Social Networks is a practical book on how to collect, visualize, analyze and interpret social network data with a particular emphasis on the use of the software tools UCINET and Netdraw. The book includes a clear and detailed introduction to the fundamental concepts of network analyses, including centrality, subgroups, equivalence and network structure, as well as cross-cutting chapters that helpfully show how to apply network concepts to different kinds of networks. Written using simple language and notation with few equations, this book masterfully covers the research process, including: · The initial design stage · Data collection and manipulation · Measuring key variables · Exploration of structure · Hypothesis testing · Interpretation This is an essential resource for students, researchers and practitioners across the social sciences who want to use network analysis as part of their research. Available with Perusall—an eBook that makes it easier to prepare for class Perusall is an award-winning eBook platform featuring social annotation tools that allow students and instructors to collaboratively mark up and discuss their SAGE textbook. Backed by research and supported by technological innovations developed at Harvard University, this process of learning through collaborative annotation keeps your students engaged and makes teaching easier and more effective. Learn more.

Author : John McLevey
Publisher : SAGE
Page : 556 pages
File Size : 41,6 Mb
Release : 2021-12-15
Category : Social Science
ISBN : 9781529737592

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Doing Computational Social Science by John McLevey Pdf

Computational approaches offer exciting opportunities for us to do social science differently. This beginner’s guide discusses a range of computational methods and how to use them to study the problems and questions you want to research. It assumes no knowledge of programming, offering step-by-step guidance for coding in Python and drawing on examples of real data analysis to demonstrate how you can apply each approach in any discipline. The book also: Considers important principles of social scientific computing, including transparency, accountability and reproducibility. Understands the realities of completing research projects and offers advice for dealing with issues such as messy or incomplete data and systematic biases. Empowers you to learn at your own pace, with online resources including screencast tutorials and datasets that enable you to practice your skills and get up to speed. For anyone who wants to use computational methods to conduct a social science research project, this book equips you with the skills, good habits and best working practices to do rigorous, high quality work.

Author : Pa?kowska, Ma?gorzata
Publisher : IGI Global
Page : 432 pages
File Size : 53,6 Mb
Release : 2021-01-29
Category : Business & Economics
ISBN : 9781799867159

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Handbook of Research on Autopoiesis and Self-Sustaining Processes for Organizational Success by Pa?kowska, Ma?gorzata Pdf

Autopoietic systems show a remarkable property in the way they interact with their environment: on the one hand building blocks and energy (including information) are exchanged with the environment, which characterizes them as open systems; on the other hand, any functional mechanisms—the way the system processes, incorporates building blocks, and responds to information—are totally self-determined and cannot be controlled by interventions from the environment. Information systems in an organization seem to accept the autopoietic system way of development and can help managers to understand the operations of their organizations better. The Handbook of Research on Autopoiesis and Self-Sustaining Processes for Organizational Success is an innovative reference book that presents the meaning of autopoietic organizations for social and information science, examines how autopoietic organizations are information self-producing and self-controlled, and provides a framework for its development in modern organizations. The book focuses on analyzing autopoiesis features such as self-managing, self-sustaining, self-producing, self-regulating, etc. Moreover, as the aforementioned characteristics receive a new interpretation in IT environments, the book also includes an exploration of IT solutions that enable the development of these characteristics. This book is ideal for professionals, academicians, researchers, and students working in the field of information economics and management in various disciplines such as information and communication sciences, administrative sciences and management, education, computer science, and information technology.

Author : John Scott,Lecturer Department of Sociology John Scott
Publisher : SAGE
Page : 249 pages
File Size : 49,8 Mb
Release : 2017-02-16
Category : Reference
ISBN : 9781526412256

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Social Network Analysis by John Scott,Lecturer Department of Sociology John Scott Pdf

With a new chapter on social media, new worked examples and better addressing the needs of the newcomer (whilst still remaining authoritative), this fourth edition continues to be an invaluable resource in introducing readers to the theories and techniques of social network analysis.

Author : Dipanjan Sarkar
Publisher : Apress
Page : 397 pages
File Size : 53,7 Mb
Release : 2016-11-30
Category : Computers
ISBN : 9781484223888

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Text Analytics with Python by Dipanjan Sarkar Pdf

Derive useful insights from your data using Python. You will learn both basic and advanced concepts, including text and language syntax, structure, and semantics. You will focus on algorithms and techniques, such as text classification, clustering, topic modeling, and text summarization. Text Analytics with Python teaches you the techniques related to natural language processing and text analytics, and you will gain the skills to know which technique is best suited to solve a particular problem. You will look at each technique and algorithm with both a bird's eye view to understand how it can be used as well as with a microscopic view to understand the mathematical concepts and to implement them to solve your own problems. What You Will Learn: Understand the major concepts and techniques of natural language processing (NLP) and text analytics, including syntax and structure Build a text classification system to categorize news articles, analyze app or game reviews using topic modeling and text summarization, and cluster popular movie synopses and analyze the sentiment of movie reviews Implement Python and popular open source libraries in NLP and text analytics, such as the natural language toolkit (nltk), gensim, scikit-learn, spaCy and Pattern Who This Book Is For : IT professionals, analysts, developers, linguistic experts, data scientists, and anyone with a keen interest in linguistics, analytics, and generating insights from textual data

Author : Subarna Shakya,Klimis Ntalianis,Khaled A. Kamel
Publisher : Springer Nature
Page : 939 pages
File Size : 45,7 Mb
Release : 2022-07-15
Category : Technology & Engineering
ISBN : 9789811920691

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Mobile Computing and Sustainable Informatics by Subarna Shakya,Klimis Ntalianis,Khaled A. Kamel Pdf

This book gathers selected high-quality research papers presented at International Conference on Mobile Computing and Sustainable Informatics (ICMCSI 2022) organized by Pulchowk Campus, Institute of Engineering, Tribhuvan University, Nepal, during 27–28 January 2022. The book discusses recent developments in mobile communication technologies ranging from mobile edge computing devices, to personalized, embedded and sustainable applications. The book covers vital topics like mobile networks, computing models, algorithms, sustainable models and advanced informatics that supports the symbiosis of mobile computing and sustainable informatics.

Author : Paulo Shakarian,Abhivav Bhatnagar,Ashkan Aleali,Elham Shaabani,Ruocheng Guo
Publisher : Springer
Page : 101 pages
File Size : 55,7 Mb
Release : 2015-09-16
Category : Computers
ISBN : 9783319231051

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Diffusion in Social Networks by Paulo Shakarian,Abhivav Bhatnagar,Ashkan Aleali,Elham Shaabani,Ruocheng Guo Pdf

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.