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Author: Bernard J. Jansen
Publisher: Springer Nature
ISBN: 3031419332
Category : Mathematics
Languages : en
Pages : 159
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Book Description
This book presents the foundations of using analytics from the laboratory, social media platforms, and the web. The authors cover key topics including analytics strategy, data gathering approaches, data preprocessing, data quality assessment, analytical methods, tools, and validation methods. The book includes chapters explaining web analytics, social media analytics, and how to create an analytics strategy. The authors also cover on data sources, such as online surveys, crowdsourcing, eye tracking, mouse tracking, social media APIs, search logs, and analytics triangulation. The book also discusses analytical tools for social media analytics, search analytics, persona analytics, user studies, and website analytics. The authors conclude by examining the validity of online analytics.
Author: Bernard J. Jansen
Publisher: Springer Nature
ISBN: 3031419332
Category : Mathematics
Languages : en
Pages : 159
Get Book Here
Book Description
This book presents the foundations of using analytics from the laboratory, social media platforms, and the web. The authors cover key topics including analytics strategy, data gathering approaches, data preprocessing, data quality assessment, analytical methods, tools, and validation methods. The book includes chapters explaining web analytics, social media analytics, and how to create an analytics strategy. The authors also cover on data sources, such as online surveys, crowdsourcing, eye tracking, mouse tracking, social media APIs, search logs, and analytics triangulation. The book also discusses analytical tools for social media analytics, search analytics, persona analytics, user studies, and website analytics. The authors conclude by examining the validity of online analytics.
Author: Bernard J. Jansen
Publisher: Springer Nature
ISBN: 3031022319
Category : Computers
Languages : en
Pages : 317
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Book Description
Data-driven personas are a significant advancement in the fields of human-centered informatics and human-computer interaction. Data-driven personas enhance user understanding by combining the empathy inherent with personas with the rationality inherent in analytics using computational methods. Via the employment of these computational methods, the data-driven persona method permits the use of large-scale user data, which is a novel advancement in persona creation. A common approach for increasing stakeholder engagement about audiences, customers, or users, persona creation remained relatively unchanged for several decades. However, the availability of digital user data, data science algorithms, and easy access to analytics platforms provide avenues and opportunities to enhance personas from often sketchy representations of user segments to precise, actionable, interactive decision-making tools—data-driven personas! Using the data-driven approach, the persona profile can serve as an interface to a fully functional analytics system that can present user representation at various levels of information granularity for more task-aligned user insights. We trace the techniques that have enabled the development of data-driven personas and then conceptually frame how one can leverage data-driven personas as tools for both empathizing with and understanding of users. Presenting a conceptual framework consisting of (a) persona benefits, (b) analytics benefits, and (c) decision-making outcomes, we illustrate applying this framework via practical use cases in areas of system design, digital marketing, and content creation to demonstrate the application of data-driven personas in practical applied situations. We then present an overview of a fully functional data-driven persona system as an example of multi-level information aggregation needed for decision making about users. We demonstrate that data-driven personas systems can provide critical, empathetic, and user understanding functionalities for anyone needing such insights.
Author: Bernard J. Jansen
Publisher: Morgan & Claypool Publishers
ISBN: 1598298518
Category : Computers
Languages : en
Pages : 117
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Book Description
This lecture presents an overview of the Web analytics process, with a focus on providing insight and actionable outcomes from collecting and analyzing Internet data. The lecture first provides an overview of Web analytics, providing in essence, a condensed version of the entire lecture. The lecture then outlines the theoretical and methodological foundations of Web analytics in order to make obvious the strengths and shortcomings of Web analytics as an approach. These foundational elements include the psychological basis in behaviorism and methodological underpinning of trace data as an empirical method. These foundational elements are illuminated further through a brief history of Web analytics from the original transaction log studies in the 1960s through the information science investigations of library systems to the focus on Websites, systems, and applications. Following a discussion of on-going interaction data within the clickstream created using log files and page tagging for analytics of Website and search logs, the lecture then presents a Web analytic process to convert these basic data to meaningful key performance indicators in order to measure likely converts that are tailored to the organizational goals or potential opportunities. Supplementary data collection techniques are addressed, including surveys and laboratory studies. The overall goal of this lecture is to provide implementable information and a methodology for understanding Web analytics in order to improve Web systems, increase customer satisfaction, and target revenue through effective analysis of user-Website interactions. Table of Contents: Understanding Web Analytics / The Foundations of Web Analytics: Theory and Methods / The History of Web Analytics / Data Collection for Web Analytics / Web Analytics Fundamentals / Web Analytics Strategy / Web Analytics as Competitive Intelligence / Supplementary Methods for Augmenting Web Analytics / Search Log Analytics / Conclusion / Key Terms / Blogs for Further Reading / References
Author: C. Ann Hollifield
Publisher: Taylor & Francis
ISBN: 0429015860
Category : Language Arts & Disciplines
Languages : en
Pages : 364
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Book Description
This textbook takes a case study approach to media and audience analytics. Realizing the best way to understand analytics in the digital age is to practice it, the authors have created a collection of cases using datasets that present real and hypothetical scenarios for students to work through. Media Analytics introduces the key principles of media economics and management. It outlines how to interpret and present results, the principles of data visualization and storytelling, and the basics of research design and sampling. Although shifting technology makes measurement and analytics a dynamic space, this book takes an evergreen, conceptual approach, reminding students to focus on the principles and foundations that will remain constant. Aimed at upper-level students in the fast-growing area of media analytics in a cross-platform world, students using this text will learn how to find the stories in the data and how to present those stories in an engaging way to others. Instructor and Student Resources include an Instructor’s Manual, discussion questions, short exercises, and links to additional resources. They are available online at www.routledge.com/cw/hollifield.
Author: Lee Wilson
Publisher: Emerald Group Publishing
ISBN: 1789738172
Category : Business & Economics
Languages : en
Pages : 192
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Book Description
This practical content guide empowers businesses to understand, identify and act on big-data opportunities, producing superior business insights for prolific marketing gains.
Author: Lillian Pierson
Publisher: John Wiley & Sons
ISBN: 1119327652
Category : Computers
Languages : en
Pages : 408
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Book Description
Discover how data science can help you gain in-depth insight into your business - the easy way! Jobs in data science abound, but few people have the data science skills needed to fill these increasingly important roles. Data Science For Dummies is the perfect starting point for IT professionals and students who want a quick primer on all areas of the expansive data science space. With a focus on business cases, the book explores topics in big data, data science, and data engineering, and how these three areas are combined to produce tremendous value. If you want to pick-up the skills you need to begin a new career or initiate a new project, reading this book will help you understand what technologies, programming languages, and mathematical methods on which to focus. While this book serves as a wildly fantastic guide through the broad, sometimes intimidating field of big data and data science, it is not an instruction manual for hands-on implementation. Here’s what to expect: Provides a background in big data and data engineering before moving on to data science and how it's applied to generate value Includes coverage of big data frameworks like Hadoop, MapReduce, Spark, MPP platforms, and NoSQL Explains machine learning and many of its algorithms as well as artificial intelligence and the evolution of the Internet of Things Details data visualization techniques that can be used to showcase, summarize, and communicate the data insights you generate It's a big, big data world out there—let Data Science For Dummies help you harness its power and gain a competitive edge for your organization.
Author: Don Grady
Publisher: Routledge
ISBN: 1000721728
Category : Language Arts & Disciplines
Languages : en
Pages : 241
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Book Description
Audience and media analytics is more important now than ever, and this latest volume in the cutting-edge BEA Electronic Media Research Series collects some of the top scholars working with big data and analytics today. These chapters describe the development and help define media analytics as an academic discipline and professional practice. Understanding audiences is integral to creating and distributing media messages and the study of media analytics requires knowing a range of skills including research methods, the necessary tools available, familiarity with statistical procedures, and a mindset to provide insights and apply findings. This book summarizes the insights of analytics practitioners regarding the current state of legacy media analysis and social media analytics. Topics covered include the evolution of media technologies, the teaching of media measurement and analytics, the transition taking place in media research, and the use of media analytics to answer meaningful questions, drive content creation, and engage with audiences.
Author: City of London College of Economics
Publisher: City of London College of Economics
ISBN:
Category : Education
Languages : en
Pages : 2653
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Book Description
Overview This diploma course covers all aspects you need to know to become a successful Data Scientist. Content - Getting Started with Data Science - Data Analytic Thinking - Business Problems and Data Science Solutions - Introduction to Predictive Modeling: From Correlation to Supervised Segmentation - Fitting a Model to Data - Overfitting and Its Avoidance - Similarity, Neighbors, and Clusters Decision Analytic Thinking I: What Is a Good Model? - Visualizing Model Performance - Evidence and Probabilities - Representing and Mining Text - Decision Analytic Thinking II: Toward Analytical Engineering - Other Data Science Tasks and Techniques - Data Science and Business Strategy - Machine Learning: Learning from Data with Your Machine. - And much more Duration 6 months Assessment The assessment will take place on the basis of one assignment at the end of the course. Tell us when you feel ready to take the exam and we’ll send you the assignment questions. Study material The study material will be provided in separate files by email / download link.
Author: Ulrike Rohn
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110793490
Category : Business & Economics
Languages : en
Pages : 477
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Book Description
The handbook presents key contributions from scholars worldwide, providing a comprehensive exploration of current trends in media industries from diverse perspectives. Within the framework of understanding contemporary and future trajectories in media markets and industries, the volume delves into their influence on media organization and delivery, along with broader societal and market implications. Encompassing research at the crossroads of economics, management, political economy, and production studies, the handbook emphasizes the necessity for a robust interdisciplinary dialogue. Beyond scrutinizing present and forthcoming industry developments, the handbook addresses pivotal issues pertaining to media economics research methods and pedagogy. It serves as a valuable resource for scholars, students, and media professionals, providing insights into media economics as an academic field and delving into the multifaceted dynamics that shape the media landscape. Doing this, it contributes to the ongoing discourse on the evolving nature of media markets and their profound impact on society.
Author: Federico Galli
Publisher: Springer Nature
ISBN: 3031136039
Category : Law
Languages : en
Pages : 280
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Book Description
Artificial Intelligence (AI) systems are increasingly being deployed by marketing entities in connection with consumers’ interactions. Thanks to machine learning (ML) and cognitive computing technologies, businesses can now analyse vast amounts of data on consumers, generate new knowledge, use it to optimize certain processes, and undertake tasks that were previously impossible. Against this background, this book analyses new algorithmic commercial practices, discusses their challenges for consumers, and measures such developments against the current EU legislative framework on consumer protection. The book adopts an interdisciplinary approach, building on empirical findings from AI applications in marketing and theoretical insights from marketing studies, and combining them with normative analysis of privacy and consumer protection in the EU. The content is divided into three parts. The first part analyses the phenomenon of algorithmic marketing practices and reviews the main AI and AI-related technologies used in marketing, e.g. Big data, ML and NLP. The second part describes new commercial practices, including the massive monitoring and profiling of consumers, the personalization of advertising and offers, the exploitation of psychological and emotional insights, and the use of human-like interfaces to trigger emotional responses. The third part provides a comprehensive analysis of current EU consumer protection laws and policies in the field of commercial practices. It focuses on two main legal concepts, their shortcomings, and potential refinements: vulnerability, understood as the conceptual benchmark for protecting consumers from unfair algorithmic practices; manipulation, the substantive legal measure for drawing the line between fair and unfair practices.
