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

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.

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

If you want your startup to succeed, you need to understand why startups fail. “Whether you’re a first-time founder or looking to bring innovation into a corporate environment, Why Startups Fail is essential reading.”—Eric Ries, founder and CEO, LTSE, and New York Times bestselling author of The Lean Startup and The Startup Way Why do startups fail? That question caught Harvard Business School professor Tom Eisenmann by surprise when he realized he couldn’t answer it. So he launched a multiyear research project to find out. In Why Startups Fail, Eisenmann reveals his findings: six distinct patterns that account for the vast majority of startup failures. • Bad Bedfellows. Startup success is thought to rest largely on the founder’s talents and instincts. But the wrong team, investors, or partners can sink a venture just as quickly. • False Starts. In following the oft-cited advice to “fail fast” and to “launch before you’re ready,” founders risk wasting time and capital on the wrong solutions. • False Promises. Success with early adopters can be misleading and give founders unwarranted confidence to expand. • Speed Traps. Despite the pressure to “get big fast,” hypergrowth can spell disaster for even the most promising ventures. • Help Wanted. Rapidly scaling startups need lots of capital and talent, but they can make mistakes that leave them suddenly in short supply of both. • Cascading Miracles. Silicon Valley exhorts entrepreneurs to dream big. But the bigger the vision, the more things that can go wrong. Drawing on fascinating stories of ventures that failed to fulfill their early promise—from a home-furnishings retailer to a concierge dog-walking service, from a dating app to the inventor of a sophisticated social robot, from a fashion brand to a startup deploying a vast network of charging stations for electric vehicles—Eisenmann offers frameworks for detecting when a venture is vulnerable to these patterns, along with a wealth of strategies and tactics for avoiding them. A must-read for founders at any stage of their entrepreneurial journey, Why Startups Fail is not merely a guide to preventing failure but also a roadmap charting the path to startup success.

This first-rate introduction to the study of social networks combines a hands-on manual with an up-to-date review of the latest research and techniques. The authors provide a thorough grounding in the application of the methods of social network analysis. They offer an understanding of the theory of social structures in which social network analysis is grounded, a summary of the concepts needed for dealing with more advanced techniques, and guides for using the primary computer software packages for social network analysis.

The Handbook of Entrepreneurship Research: Disciplinary Perspectives strives to increase awareness and stimulate research in numerous important topics in the field, particularly those underdeveloped areas of study with more relevance to scholarship and theory than to the practice of entrepreneurship. For example, less research has focused on the importance of the macroeconomic environment to firm founding, on social and kinship ties as sources of entrepreneurial activity, and the interaction between institutions and entrepreneurship. We do so by drawing attention to the relevant research in the disciplines of economics and sociology. This volume of the Handbook hopes to begin to bridge the gap between the research in entrepreneurship and the core disciplines by introducing views of entrepreneurship from disciplinary perspectives. As such, this volume of the Handbook is intended to complement and build on the first volume by focusing on a select set of issues and examining them in an in-depth manner.

Doing research is an ever-changing challenge for social scientists. This challenge is harder than ever today as current societies are changing quickly and in many, sometimes conflicting, directions. Social phenomena, personal interactions, and formal and informal relationships are becoming more borderless and disconnected from the anchors of the offline “reality.” These dynamics are heavily marking our time and are suggesting evolutionary challenges in the ways we know, interpret, and analyze the world. Internet and computer-mediated communication (CMC) is being incorporated into every aspect of daily life, and social life has been deeply penetrated by the internet. This is due to recent technological developments that increase the scope and range of online social spaces and the forms and time of participation such as Web 2.0, which widened the opportunities for user-generated content, the emergence of an “internet of things,” and of ubiquitous mobile devices that make it possible to always be connected. This implies an adjustment to epistemological and methodological stances for conducting social research and an adaption of traditional social research methods to the specificities of online interactions in the digital society. The Handbook of Research on Advanced Research Methodologies for a Digital Society covers the different strands of methods most affected by the change in a digital society and develops a broader theoretical reflection on the future of social research in its challenge to always be fitting, suitable, adaptable, and pertinent to the society to be studied. The chapters are geared towards unlocking the future frontiers and potential for social research in the digital society. They include theoretical, epistemological, and ontological reflections about the digital research methods as well as innovative methods and tools to collect, analyze, and interpret data. This book is ideal for social scientists, practitioners, librarians, researchers, academicians, and students interested in social research methodology and its developments in the digital scenario.

Social networking is a concept that has existed for a long time; however, with the explosion of the Internet, social networking has become a tool for people to connect and communicate in ways that were impossible in the past. The recent development of Web 2.0 has provided many new applications, such as Myspace, Facebook, and LinkedIn. The purpose of Handbook of Social Network Technologies and Applications is to provide comprehensive guidelines on the current and future trends in social network technologies and applications in the field of Web-based Social Networks. This handbook includes contributions from world experts in the field of social networks from both academia and private industry. A number of crucial topics are covered including Web and software technologies and communication technologies for social networks. Web-mining techniques, visualization techniques, intelligent social networks, Semantic Web, and many other topics are covered. Standards for social networks, case studies, and a variety of applications are covered as well.

With business advice from an expert entrepreneur, learn how to identify and leverage the key factors that will bring sustainability and success to your startup. Kathleen Kelly Janus, a lecturer at the Stanford University Program on Social Entrepreneurship and the founder of the successful social enterprise Spark, set out to investigate what makes a startup succeed or fail. She surveyed more than 200 high-performing social entrepreneurs and interviewed dozens of founders. Social Startup Success shares her findings for the legions of entrepreneurs working for social good, revealing how the best organizations get over the revenue hump. How do social ventures scale to over $2 million, Janus's clear benchmark for a social enterprise's sustainability? ​Janus, tapping into strong connections to the Silicon Valley world where many of these ventures are started or and/or funded, reveals insights from key figures such as DonorsChoose founder Charles Best, charity:water's Scott Harrison, Reshma Saujani of Girls Who Code and many others. Social Startup Success will be social entrepreneurship's essential playbook; the first definitive guide to solving the problem of scale.

Whether you're a startup founder trying to disrupt an industry or an entrepreneur trying to provoke change from within, your biggest challenge is creating a product people actually want. Lean Analytics steers you in the right direction. This book shows you how to validate your initial idea, find the right customers, decide what to build, how to monetize your business, and how to spread the word. Packed with more than thirty case studies and insights from over a hundred business experts, Lean Analytics provides you with hard-won, real-world information no entrepreneur can afford to go without. Understand Lean Startup, analytics fundamentals, and the data-driven mindset Look at six sample business models and how they map to new ventures of all sizes Find the One Metric That Matters to you Learn how to draw a line in the sand, so you'll know it's time to move forward Apply Lean Analytics principles to large enterprises and established products