Download Social Data Analytics Book PDF

Download full Social Data Analytics books PDF, EPUB, Tuebl, Textbook, Mobi or read online Social Data Analytics anytime and anywhere on any device. Get free access to the library by create an account, fast download and ads free. We cannot guarantee that every book is in the library.

• Author : Krish Krishnan,Shawn P. Rogers
• Publisher :Unknown
• Release Date :2014-11-10
• Total pages :158
• ISBN : 9780123977809

GET BOOK HERE

Summary : Social Data Analytics is the first practical guide for professionals who want to employ social data for analytics and business intelligence (BI). This book provides a comprehensive overview of the technologies and platforms and shows you how to access and analyze the data. You'll explore the five major types of social data and learn from cases and platform examples to help you make the most of sentiment, behavioral, social graph, location, and rich media data. A four-step approach to the social BI process will help you access, evaluate, collaborate, and share social data with ease. You'll learn everything you need to know to monitor social media and get an overview of the leading vendors in a crowded space of BI applications. By the end of this book, you will be well prepared for your organization’s next social data analytics project. Provides foundational understanding of new and emerging technologies—social data, collaboration, big data, advanced analytics Includes case studies and practical examples of success and failures Will prepare you to lead projects and advance initiatives that will benefit you and your organization

• Author : Mohamed Ali Bin Saip
• Publisher :Unknown
• Release Date :2019
• Total pages :249
• ISBN : OCLC:1179768959

GET BOOK HERE

Summary :

• Author : Charu C. Aggarwal
• Publisher :Unknown
• Release Date :2011-03-18
• Total pages :502
• ISBN : 9781441984623

GET BOOK HERE

Summary : Social network analysis applications have experienced tremendous advances within the last few years due in part to increasing trends towards users interacting with each other on the internet. Social networks are organized as graphs, and the data on social networks takes on the form of massive streams, which are mined for a variety of purposes. Social Network Data Analytics covers an important niche in the social network analytics field. This edited volume, contributed by prominent researchers in this field, presents a wide selection of topics on social network data mining such as Structural Properties of Social Networks, Algorithms for Structural Discovery of Social Networks and Content Analysis in Social Networks. This book is also unique in focussing on the data analytical aspects of social networks in the internet scenario, rather than the traditional sociology-driven emphasis prevalent in the existing books, which do not focus on the unique data-intensive characteristics of online social networks. Emphasis is placed on simplifying the content so that students and practitioners benefit from this book. This book targets advanced level students and researchers concentrating on computer science as a secondary text or reference book. Data mining, database, information security, electronic commerce and machine learning professionals will find this book a valuable asset, as well as primary associations such as ACM, IEEE and Management Science.

• Author : Mrutyunjaya Panda,Ajith Abraham,Aboul Ella Hassanien
• Publisher :Unknown
• Release Date :2018-12-12
• Total pages :316
• ISBN : 9781351622592

GET BOOK HERE

Summary : Social networking has increased drastically in recent years, resulting in an increased amount of data being created daily. Furthermore, diversity of issues and complexity of the social networks pose a challenge in social network mining. Traditional algorithm software cannot deal with such complex and vast amounts of data, necessitating the development of novel analytic approaches and tools. This reference work deals with social network aspects of big data analytics. It covers theory, practices and challenges in social networking. The book spans numerous disciplines like neural networking, deep learning, artificial intelligence, visualization, e-learning in higher education, e-healthcare, security and intrusion detection.

• Author : Sathiyamoorthi, V.,Elci, Atilla
• Publisher :Unknown
• Release Date :2020-12-04
• Total pages :324
• ISBN : 9781799825685

GET BOOK HERE

Summary : With exponentially increasing amounts of data accumulating in real-time, there is no reason why one should not turn data into a competitive advantage. While machine learning, driven by advancements in artificial intelligence, has made great strides, it has not been able to surpass a number of challenges that still prevail in the way of better success. Such limitations as the lack of better methods, deeper understanding of problems, and advanced tools are hindering progress. Challenges and Applications of Data Analytics in Social Perspectives provides innovative insights into the prevailing challenges in data analytics and its application on social media and focuses on various machine learning and deep learning techniques in improving practice and research. The content within this publication examines topics that include collaborative filtering, data visualization, and edge computing. It provides research ideal for data scientists, data analysts, IT specialists, website designers, e-commerce professionals, government officials, software engineers, social media analysts, industry professionals, academicians, researchers, and students.

• Author : Siddhartha Chatterjee,Michal Krystyanczuk
• Publisher :Unknown
• Release Date :2017-07-28
• Total pages :312
• ISBN : 9781787126756

GET BOOK HERE

Summary : Leverage the power of Python to collect, process, and mine deep insights from social media data About This Book Acquire data from various social media platforms such as Facebook, Twitter, YouTube, GitHub, and more Analyze and extract actionable insights from your social data using various Python tools A highly practical guide to conducting efficient social media analytics at scale Who This Book Is For If you are a programmer or a data analyst familiar with the Python programming language and want to perform analyses of your social data to acquire valuable business insights, this book is for you. The book does not assume any prior knowledge of any data analysis tool or process. What You Will Learn Understand the basics of social media mining Use PyMongo to clean, store, and access data in MongoDB Understand user reactions and emotion detection on Facebook Perform Twitter sentiment analysis and entity recognition using Python Analyze video and campaign performance on YouTube Mine popular trends on GitHub and predict the next big technology Extract conversational topics on public internet forums Analyze user interests on Pinterest Perform large-scale social media analytics on the cloud In Detail Social Media platforms such as Facebook, Twitter, Forums, Pinterest, and YouTube have become part of everyday life in a big way. However, these complex and noisy data streams pose a potent challenge to everyone when it comes to harnessing them properly and benefiting from them. This book will introduce you to the concept of social media analytics, and how you can leverage its capabilities to empower your business. Right from acquiring data from various social networking sources such as Twitter, Facebook, YouTube, Pinterest, and social forums, you will see how to clean data and make it ready for analytical operations using various Python APIs. This book explains how to structure the clean data obtained and store in MongoDB using PyMongo. You will also perform web scraping and visualize data using Scrappy and Beautifulsoup. Finally, you will be introduced to different techniques to perform analytics at scale for your social data on the cloud, using Python and Spark. By the end of this book, you will be able to utilize the power of Python to gain valuable insights from social media data and use them to enhance your business processes. Style and approach This book follows a step-by-step approach to teach readers the concepts of social media analytics using the Python programming language. To explain various data analysis processes, real-world datasets are used wherever required.

• Author : Christos Doulkeridis,George A. Vouros,Qiang Qu,Shuhui Wang
• Publisher :Unknown
• Release Date :2018-02-01
• Total pages :177
• ISBN : 9783319735214

GET BOOK HERE

Summary : This book constitutes the refereed post-conference proceedings of the First International Workshop on Mobility Analytics for Spatio-Temporal and Social Data, MATES 2017, held in Munich, Germany, in September 2017. The 6 revised full papers and 2 short papers included in this volume were carefully reviewed and selected from 13 submissions. Also included are two keynote speeches. The papers intend to raise awareness of real-world problems in critical domains which require novel data management solutions. They are organized in two thematic sections: social network analytics and applications, and spatio-temporal mobility analytics.

• Author : Charu C. Aggarwal
• Publisher :Unknown
• Release Date :2011-03-18
• Total pages :502
• ISBN : 9781441984623

GET BOOK HERE

Summary : Social network analysis applications have experienced tremendous advances within the last few years due in part to increasing trends towards users interacting with each other on the internet. Social networks are organized as graphs, and the data on social networks takes on the form of massive streams, which are mined for a variety of purposes. Social Network Data Analytics covers an important niche in the social network analytics field. This edited volume, contributed by prominent researchers in this field, presents a wide selection of topics on social network data mining such as Structural Properties of Social Networks, Algorithms for Structural Discovery of Social Networks and Content Analysis in Social Networks. This book is also unique in focussing on the data analytical aspects of social networks in the internet scenario, rather than the traditional sociology-driven emphasis prevalent in the existing books, which do not focus on the unique data-intensive characteristics of online social networks. Emphasis is placed on simplifying the content so that students and practitioners benefit from this book. This book targets advanced level students and researchers concentrating on computer science as a secondary text or reference book. Data mining, database, information security, electronic commerce and machine learning professionals will find this book a valuable asset, as well as primary associations such as ACM, IEEE and Management Science.

• Author : Raghav Bali,Dipanjan Sarkar,Tushar Sharma
• Publisher :Unknown
• Release Date :2017-05-26
• Total pages :394
• ISBN : 9781787125469

GET BOOK HERE

Summary : Tap into the realm of social media and unleash the power of analytics for data-driven insights using R About This Book A practical guide written to help leverage the power of the R eco-system to extract, process, analyze, visualize and model social media data Learn about data access, retrieval, cleaning, and curation methods for data originating from various social media platforms. Visualize and analyze data from social media platforms to understand and model complex relationships using various concepts and techniques such as Sentiment Analysis, Topic Modeling, Text Summarization, Recommendation Systems, Social Network Analysis, Classification, and Clustering. Who This Book Is For It is targeted at IT professionals, Data Scientists, Analysts, Developers, Machine Learning Enthusiasts, social media marketers and anyone with a keen interest in data, analytics, and generating insights from social data. Some background experience in R would be helpful, but not necessary, since this book is written keeping in mind, that readers can have varying levels of expertise. What You Will Learn Learn how to tap into data from diverse social media platforms using the R ecosystem Use social media data to formulate and solve real-world problems Analyze user social networks and communities using concepts from graph theory and network analysis Learn to detect opinion and sentiment, extract themes, topics, and trends from unstructured noisy text data from diverse social media channels Understand the art of representing actionable insights with effective visualizations Analyze data from major social media channels such as Twitter, Facebook, Flickr, Foursquare, Github, StackExchange, and so on Learn to leverage popular R packages such as ggplot2, topicmodels, caret, e1071, tm, wordcloud, twittR, Rfacebook, dplyr, reshape2, and many more In Detail The Internet has truly become humongous, especially with the rise of various forms of social media in the last decade, which give users a platform to express themselves and also communicate and collaborate with each other. This book will help the reader to understand the current social media landscape and to learn how analytics can be leveraged to derive insights from it. This data can be analyzed to gain valuable insights into the behavior and engagement of users, organizations, businesses, and brands. It will help readers frame business problems and solve them using social data. The book will also cover several practical real-world use cases on social media using R and its advanced packages to utilize data science methodologies such as sentiment analysis, topic modeling, text summarization, recommendation systems, social network analysis, classification, and clustering. This will enable readers to learn different hands-on approaches to obtain data from diverse social media sources such as Twitter and Facebook. It will also show readers how to establish detailed workflows to process, visualize, and analyze data to transform social data into actionable insights. Style and approach This book follows a step-by-step approach with detailed strategies for understanding, extracting, analyzing, visualizing, and modeling data from several major social network platforms such as Facebook, Twitter, Foursquare, Flickr, Github, and StackExchange. The chapters cover several real-world use cases and leverage data science, machine learning, network analysis, and graph theory concepts along with the R ecosystem, including popular packages such as ggplot2, caret,dplyr, topicmodels, tm, and so on.

• Author : Haldorai, Anandakumar,Ramu, Arulmurugan
• Publisher :Unknown
• Release Date :2018-12-14
• Total pages :326
• ISBN : 9781522575238

GET BOOK HERE

Summary : Recently, there has been a rapid increase in interest regarding social network analysis in the data mining community. Cognitive radios are expected to play a major role in meeting this exploding traffic demand on social networks due to their ability to sense the environment, analyze outdoor parameters, and then make decisions for dynamic time, frequency, space, resource allocation, and management to improve the utilization of mining the social data. Cognitive Social Mining Applications in Data Analytics and Forensics is an essential reference source that reviews cognitive radio concepts and examines their applications to social mining using a machine learning approach so that an adaptive and intelligent mining is achieved. Featuring research on topics such as data mining, real-time ubiquitous social mining services, and cognitive computing, this book is ideally designed for social network analysts, researchers, academicians, and industry professionals.

• Author : Gabor Szabo,Gungor Polatkan,P. Oscar Boykin,Antonios Chalkiopoulos
• Publisher :Unknown
• Release Date :2018-09-19
• Total pages :352
• ISBN : 9781118824894

GET BOOK HERE

Summary : Harness the power of social media to predict customer behavior and improve sales Social media is the biggest source of Big Data. Because of this, 90% of Fortune 500 companies are investing in Big Data initiatives that will help them predict consumer behavior to produce better sales results. Social Media Data Mining and Analytics shows analysts how to use sophisticated techniques to mine social media data, obtaining the information they need to generate amazing results for their businesses. Social Media Data Mining and Analytics isn't just another book on the business case for social media. Rather, this book provides hands-on examples for applying state-of-the-art tools and technologies to mine social media - examples include Twitter, Wikipedia, Stack Exchange, LiveJournal, movie reviews, and other rich data sources. In it, you will learn: The four key characteristics of online services-users, social networks, actions, and content The full data discovery lifecycle-data extraction, storage, analysis, and visualization How to work with code and extract data to create solutions How to use Big Data to make accurate customer predictions How to personalize the social media experience using machine learning Using the techniques the authors detail will provide organizations the competitive advantage they need to harness the rich data available from social media platforms.

• Author : Bilal Abu-Salih,Pornpit Wongthongtham,Dengya Zhu,Kit Yan Chan,Amit Rudra
• Publisher :Unknown
• Release Date :2021-03-18
• Total pages :229
• ISBN : 9813366516

GET BOOK HERE

Summary : This book focuses on data and how modern business firms use social data, specifically Online Social Networks (OSNs) incorporated as part of the infrastructure for a number of emerging applications such as personalized recommendation systems, opinion analysis, expertise retrieval, and computational advertising. This book identifies how in such applications, social data offers a plethora of benefits to enhance the decision making process. This book highlights that business intelligence applications are more focused on structured data; however, in order to understand and analyse the social big data, there is a need to aggregate data from various sources and to present it in a plausible format. Big Social Data (BSD) exhibit all the typical properties of big data: wide physical distribution, diversity of formats, non-standard data models, independently-managed and heterogeneous semantics but even further valuable with marketing opportunities. The book provides a review of the current state-of-the-art approaches for big social data analytics as well as to present dissimilar methods to infer value from social data. The book further examines several areas of research that benefits from the propagation of the social data. In particular, the book presents various technical approaches that produce data analytics capable of handling big data features and effective in filtering out unsolicited data and inferring a value. These approaches comprise advanced technical solutions able to capture huge amounts of generated data, scrutinise the collected data to eliminate unwanted data, measure the quality of the inferred data, and transform the amended data for further data analysis. Furthermore, the book presents solutions to derive knowledge and sentiments from BSD and to provide social data classification and prediction. The approaches in this book also incorporate several technologies such as semantic discovery, sentiment analysis, affective computing and machine learning. This book has additional special feature enriched with numerous illustrations such as tables, graphs and charts incorporating advanced visualisation tools in accessible an attractive display.

• Author : Haldorai, Anandakumar,Ramu, Arulmurugan
• Publisher :Unknown
• Release Date :2019-09-20
• Total pages :263
• ISBN : 9781522597520

GET BOOK HERE

Summary : Big data consists of data sets that are too large and complex for traditional data processing and data management applications. Therefore, to obtain the valuable information within the data, one must use a variety of innovative analytical methods, such as web analytics, machine learning, and network analytics. As the study of big data becomes more popular, there is an urgent demand for studies on high-level computational intelligence and computing services for analyzing this significant area of information science. Big Data Analytics for Sustainable Computing is a collection of innovative research that focuses on new computing and system development issues in emerging sustainable applications. Featuring coverage on a wide range of topics such as data filtering, knowledge engineering, and cognitive analytics, this publication is ideally designed for data scientists, IT specialists, computer science practitioners, computer engineers, academicians, professionals, and students seeking current research on emerging analytical techniques and data processing software.

• Author : Martin Atzmueller,Alvin Chin,Frederik Janssen,Immanuel Schweizer,Christoph Trattner
• Publisher :Unknown
• Release Date :2016-01-06
• Total pages :187
• ISBN : 9783319290096

GET BOOK HERE

Summary : The 9 papers presented in this book are revised and significantly extended versions of papers submitted to three related workshops: The 5th International Workshop on Mining Ubiquitous and Social Environments, MUSE 2014, and the First International Workshop on Machine Learning for Urban Sensor Data, SenseML 2014, which were held on September 15, 2014, in conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2014) in Nancy, France; and the 5th International Workshop on Modeling Social Media (MSM 2014) that was held on April 8, 2014 in conjunction with ACM WWW in Seoul, Korea.

• Author : Nilanjan Dey,Samarjeet Borah,Rosalina Babo,Amira S. Ashour
• Publisher :Unknown
• Release Date :2018-11-16
• Total pages :267
• ISBN : 9780128156414

GET BOOK HERE

Summary : Social Network Analytics: Computational Research Methods and Techniques focuses on various technical concepts and aspects of social network analysis. The book features the latest developments and findings in this emerging area of research. In addition, it includes a variety of applications from several domains, such as scientific research, and the business and industrial sectors. The technical aspects of analysis are covered in detail, including visualizing and modeling, network theory, mathematical models, the big data analytics of social networks, multidimensional scaling, and more. As analyzing social network data is rapidly gaining interest in the scientific research community because of the importance of the information and insights that can be culled from the wealth of data inherent in the various aspects of the network, this book provides insights on measuring the relationships and flows between people, groups, organizations, computers, URLs, and more. Examines a variety of data analytic techniques that can be applied to social networks Discusses various methods of visualizing, modeling and tracking network patterns, organization, growth and change Covers the most recent research on social network analysis and includes applications to a number of domains

• Author : Peter Zadrozny,Raghu Kodali
• Publisher :Unknown
• Release Date :2013-08-23
• Total pages :376
• ISBN : 9781430257622

GET BOOK HERE

Summary : Big Data Analytics Using Splunk is a hands-on book showing how to process and derive business value from big data in real time. Examples in the book draw from social media sources such as Twitter (tweets) and Foursquare (check-ins). You also learn to draw from machine data, enabling you to analyze, say, web server log files and patterns of user access in real time, as the access is occurring. Gone are the days when you need be caught out by shifting public opinion or sudden changes in customer behavior. Splunk’s easy to use engine helps you recognize and react in real time, as events are occurring. Splunk is a powerful, yet simple analytical tool fast gaining traction in the fields of big data and operational intelligence. Using Splunk, you can monitor data in real time, or mine your data after the fact. Splunk’s stunning visualizations aid in locating the needle of value in a haystack of a data. Geolocation support spreads your data across a map, allowing you to drill down to geographic areas of interest. Alerts can run in the background and trigger to warn you of shifts or events as they are taking place. With Splunk you can immediately recognize and react to changing trends and shifting public opinion as expressed through social media, and to new patterns of eCommerce and customer behavior. The ability to immediately recognize and react to changing trends provides a tremendous advantage in today’s fast-paced world of Internet business. Big Data Analytics Using Splunk opens the door to an exciting world of real-time operational intelligence. Built around hands-on projects Shows how to mine social media Opens the door to real-time operational intelligence

• Author : Marshall Sponder
• Publisher :Unknown
• Release Date :2011-09-02
• Total pages :320
• ISBN : 9780071768627

GET BOOK HERE

Summary : Align Strategy With Metrics Using Social Monitoring Best Practices “Two or three years from now, every public relations firm that wants to be taken seriously in the C-suite and/or a lead marketing role will have someone like Marshall in its senior leadership ranks, a chief analytics officer responsible for ensuring that account leaders think more deeply about analytics and that thfirm works with the best available outside suppliers to integrate analytics appropriately.” —Paul Holmes, The Holmes Report “Marshall has provided much-needed discipline to our newest marketing frontier—a territory full of outlaws, medicine men, dot com tumbleweeds, and snake oil.” —Ryan Rasmussen, VP Research, Zócalo Group “Marshall Sponder stands apart from the crowd with this work. His case study approach, borne of real-world experience, provides the expert and the amateur alike with bibliography, tools, links, and examples to shortcut the path to bedrock successes. This is a reference work for anyone who wants to explore the potential of social networks.” —W. Reid Cornwell, Ph.D., Chief Scientist, The Center for Internet Research “Marshall is a solutions design genius of unparalleled knowledge and acumen, and when he applies himself to the business of social media, the result is a timely and important commentary on the state of research capabilities for social media.” —Barry Fleming, Director, Analytics & Insights, WCG, and Principal, DharmaBuilt.com About the Book Practically overnight, social media has become a critical tool for every marketing objective—from outreach and customer relations to branding and crisis management. For the most part, however, the data collected through social media is just that: data. It usually seems to hold little or no meaning on which to base business decisions. But the meaning is there . . . if you’re applying the right systems and know how to use them. With Social Media Analytics, you’ll learn how to get supremely valuable information from this revolutionary new marketing tool. One of the most respected leaders in his field and a pioneer in Web analytics, Marshall Sponder shows how to: Choose the best social media platforms for your needs Set up the right processes to achieve your goals Extract the hidden meaning from all the data you collect Quantify your results and determine ROI Filled with in-depth case studies from a range of industries, along with detailed reviews of several social-monitoring platforms, Social Media Analytics takes you beyond “up-to-date” and leads you well into the future—and far ahead of your competition. You will learn how to use the most sophisticated methods yet known to find customers, create relevant content (and track it), mash up data from disparate sources, and much more. Sponder concludes with an insightful look at where the field will likely be going during the next few years. Whether your social media marketing efforts are directed at B2B, B2C, C2C, nonprofit, corporate, or public sector aims, take them to the next step with the techniques, strategies, and methods in Social Media Analytics—the most in-depth, forward-looking book on the subject.

• Author : Arun Reddy Nelakurthi,Jingrui He
• Publisher :Unknown
• Release Date :2020-01-21
• Total pages :98
• ISBN : 9781000025361

GET BOOK HERE

Summary : In recent years social media has gained significant popularity and has become an essential medium of communication. Such user-generated content provides an excellent scenario for applying the metaphor of mining any information. Transfer learning is a research problem in machine learning that focuses on leveraging the knowledge gained while solving one problem and applying it to a different, but related problem. Features: Offers novel frameworks to study user behavior and for addressing and explaining task heterogeneity Presents a detailed study of existing research Provides convergence and complexity analysis of the frameworks Includes algorithms to implement the proposed research work Covers extensive empirical analysis Social Media Analytics for User Behavior Modeling: A Task Heterogeneity Perspective is a guide to user behavior modeling in heterogeneous settings and is of great use to the machine learning community.

• Author : Jose Manuel Magallanes Reyes
• Publisher :Unknown
• Release Date :2017-09-21
• Total pages :303
• ISBN : 9781107117419

GET BOOK HERE

Summary : This comprehensive guide provides a step-by-step approach to data collection, cleaning, formatting, and storage, using Python and R.

• Author : Alex Gonçalves
• Publisher :Unknown
• Release Date :2017-11-12
• Total pages :306
• ISBN : 9781484231029

GET BOOK HERE

Summary : This book shows you how to use social media analytics to optimize your business performance. The tools discussed will prepare you to create and implement an effective digital marketing strategy. From understanding the data and its sources to detailed metrics, dashboards, and reports, this book is a robust tool for anyone seeking a tangible return on investment from social media and digital marketing. Social Media Analytics Strategy speaks to marketers who do not have a technical background and creates a bridge into the digital world. Comparable books are either too technical for marketers (aimed at software developers) or too basic and do not take strategy into account. They also lack an overview of the entire process around using analytics within a company project. They don’t go into the everyday details and also don’t touch upon common mistakes made by marketers. This book highlights patterns of common challenges experienced by marketers from entry level to directors and C-level executives. Social media analytics are explored and explained using real-world examples and interviews with experienced professionals and founders of social media analytics companies. What You’ll Learn Get a clear view of the available data for social media marketing and how to access all of it Make use of data and information behind social media networks to your favor Know the details of social media analytics tools and platforms so you can use any tool in the market Apply social media analytics to many different real-world use cases Obtain tips from interviews with professional marketers and founders of social media analytics platforms Understand where social media is heading, and what to expect in the future Who This Book Is For Marketing professionals, social media marketing specialists, analysts up to directors and C-level executives, marketing students, and teachers of social media analytics/social media marketing

• Author : Ian Foster,Rayid Ghani,Ron S. Jarmin,Frauke Kreuter,Julia Lane
• Publisher :Unknown
• Release Date :2016-08-10
• Total pages :376
• ISBN : 9781498751438

GET BOOK HERE

Summary : Both Traditional Students and Working Professionals Acquire the Skills to Analyze Social Problems. Big Data and Social Science: A Practical Guide to Methods and Tools shows how to apply data science to real-world problems in both research and the practice. The book provides practical guidance on combining methods and tools from computer science, statistics, and social science. This concrete approach is illustrated throughout using an important national problem, the quantitative study of innovation. The text draws on the expertise of prominent leaders in statistics, the social sciences, data science, and computer science to teach students how to use modern social science research principles as well as the best analytical and computational tools. It uses a real-world challenge to introduce how these tools are used to identify and capture appropriate data, apply data science models and tools to that data, and recognize and respond to data errors and limitations. For more information, including sample chapters and news, please visit the author's website.