Download or read book The Predictive Power of Social Media Data written by Niels Buus Lassen and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Predictive Technology in Social Media written by Cristina Fernández-Rovira and published by CRC Press. This book was released on 2022-07-07 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: Can behaviour on social media predict future purchase patterns? Can what we click on social media foresee which political party will we vote for? Can the information we share on our wall foretell the next series I might want to watch? Can the likes on Instagram and Facebook predict the time one will spend on digital platforms in the next hour? The answer is no longer science fiction. It points to the ability of mainstream social media platforms such as Facebook and Twitter to be able to deliver specialised advertising services to highly targeted audience segments controlled by the billions of devices that flood our daily lives. At the same time, it highlights a more relevant problem: can social media guide, suggest or impose a certain behaviour or thought? Everything seems to indicate that they can do it. Predictive Technology in Social Media comprises 10 essays that reflect on the power of the predictive technology of social media in culture, entertainment, marketing, economics and politics. It shows, from a humanistic and critical perspective, the predictive possibilities of social media platforms, as well as the risks this entails for cultural plurality, everyday consumption, the monopolistic concentration of the economy and attention, and democracy. The text is an invitation to think, as citizens, about the unbridled power we have ceded to digital platforms. A new voice to warn about the greatest concentration of communicative power ever seen in the history of humanity.

Download or read book Social Network Analysis in Predictive Policing written by Mohammad A. Tayebi and published by Springer. This book was released on 2016-10-11 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on applications of social network analysis in predictive policing. Data science is used to identify potential criminal activity by analyzing the relationships between offenders to fully understand criminal collaboration patterns. Co-offending networks—networks of offenders who have committed crimes together—have long been recognized by law enforcement and intelligence agencies as a major factor in the design of crime prevention and intervention strategies. Despite the importance of co-offending network analysis for public safety, computational methods for analyzing large-scale criminal networks are rather premature. This book extensively and systematically studies co-offending network analysis as effective tool for predictive policing. The formal representation of criminological concepts presented here allow computer scientists to think about algorithmic and computational solutions to problems long discussed in the criminology literature. For each of the studied problems, we start with well-founded concepts and theories in criminology, then propose a computational method and finally provide a thorough experimental evaluation, along with a discussion of the results. In this way, the reader will be able to study the complete process of solving real-world multidisciplinary problems.

Download or read book Predictive Analytics written by Eric Siegel and published by John Wiley & Sons. This book was released on 2016-01-12 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Mesmerizing & fascinating..." —The Seattle Post-Intelligencer "The Freakonomics of big data." —Stein Kretsinger, founding executive of Advertising.com Award-winning | Used by over 30 universities | Translated into 9 languages An introduction for everyone. In this rich, fascinating — surprisingly accessible — introduction, leading expert Eric Siegel reveals how predictive analytics (aka machine learning) works, and how it affects everyone every day. Rather than a “how to” for hands-on techies, the book serves lay readers and experts alike by covering new case studies and the latest state-of-the-art techniques. Prediction is booming. It reinvents industries and runs the world. Companies, governments, law enforcement, hospitals, and universities are seizing upon the power. These institutions predict whether you're going to click, buy, lie, or die. Why? For good reason: predicting human behavior combats risk, boosts sales, fortifies healthcare, streamlines manufacturing, conquers spam, optimizes social networks, toughens crime fighting, and wins elections. How? Prediction is powered by the world's most potent, flourishing unnatural resource: data. Accumulated in large part as the by-product of routine tasks, data is the unsalted, flavorless residue deposited en masse as organizations churn away. Surprise! This heap of refuse is a gold mine. Big data embodies an extraordinary wealth of experience from which to learn. Predictive analytics (aka machine learning) unleashes the power of data. With this technology, the computer literally learns from data how to predict the future behavior of individuals. Perfect prediction is not possible, but putting odds on the future drives millions of decisions more effectively, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate. In this lucid, captivating introduction — now in its Revised and Updated edition — former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction: What type of mortgage risk Chase Bank predicted before the recession. Predicting which people will drop out of school, cancel a subscription, or get divorced before they even know it themselves. Why early retirement predicts a shorter life expectancy and vegetarians miss fewer flights. Five reasons why organizations predict death — including one health insurance company. How U.S. Bank and Obama for America calculated the way to most strongly persuade each individual. Why the NSA wants all your data: machine learning supercomputers to fight terrorism. How IBM's Watson computer used predictive modeling to answer questions and beat the human champs on TV's Jeopardy! How companies ascertain untold, private truths — how Target figures out you're pregnant and Hewlett-Packard deduces you're about to quit your job. How judges and parole boards rely on crime-predicting computers to decide how long convicts remain in prison. 182 examples from Airbnb, the BBC, Citibank, ConEd, Facebook, Ford, Google, the IRS, LinkedIn, Match.com, MTV, Netflix, PayPal, Pfizer, Spotify, Uber, UPS, Wikipedia, and more. How does predictive analytics work? This jam-packed book satisfies by demystifying the intriguing science under the hood. For future hands-on practitioners pursuing a career in the field, it sets a strong foundation, delivers the prerequisite knowledge, and whets your appetite for more. A truly omnipresent science, predictive analytics constantly affects our daily lives. Whether you are a

Download or read book Social Media Analytics Strategy written by Alex Gonçalves and published by Apress. This book was released on 2017-11-12 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Opinion Mining and Sentiment Analysis written by Bo Pang and published by Now Publishers Inc. This book was released on 2008 with total page 149 pages. Available in PDF, EPUB and Kindle. Book excerpt: This survey covers techniques and approaches that promise to directly enable opinion-oriented information-seeking systems.

Download or read book Social Media Analytics in Predicting Consumer Behavior written by Selay Ilgaz Sumer and published by CRC Press. This book was released on 2023-04-27 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information is very important for businesses. Businesses that use information correctly are successful while those that don’t, decline. Social media is an important source of data. This data brings us to social media analytics. Surveys are no longer the only way to hear the voice of consumers. With the data obtained from social media platforms, businesses can devise marketing strategies. It provides a better understanding consumer behavior. As consumers are at the center of all business activities, it is unrealistic to succeed without understanding consumption patterns. Social media analytics is useful, especially for marketers. Marketers can evaluate the data to make strategic marketing plans. Social media analytics and consumer behavior are two important issues that need to be addressed together. The book differs in that it handles social media analytics from a different perspective. It is planned that social media analytics will be discussed in detail in terms of consumer behavior in the book. The book will be useful to the students, businesses, and marketers in many aspects.

Download or read book Applied Predictive Modeling written by Max Kuhn and published by Springer Science & Business Media. This book was released on 2013-05-17 with total page 595 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. The text illustrates all parts of the modeling process through many hands-on, real-life examples, and every chapter contains extensive R code for each step of the process. This multi-purpose text can be used as an introduction to predictive models and the overall modeling process, a practitioner’s reference handbook, or as a text for advanced undergraduate or graduate level predictive modeling courses. To that end, each chapter contains problem sets to help solidify the covered concepts and uses data available in the book’s R package. This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics.

Download or read book Predictive Marketing written by Omer Artun and published by John Wiley & Sons. This book was released on 2015-08-06 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: Make personalized marketing a reality with this practical guide to predictive analytics Predictive Marketing is a predictive analytics primer for organizations large and small, offering practical tips and actionable strategies for implementing more personalized marketing immediately. The marketing paradigm is changing, and this book provides a blueprint for navigating the transition from creative- to data-driven marketing, from one-size-fits-all to one-on-one, and from marketing campaigns to real-time customer experiences. You'll learn how to use machine-learning technologies to improve customer acquisition and customer growth, and how to identify and re-engage at-risk or lapsed customers by implementing an easy, automated approach to predictive analytics. Much more than just theory and testament to the power of personalized marketing, this book focuses on action, helping you understand and actually begin using this revolutionary approach to the customer experience. Predictive analytics can finally make personalized marketing a reality. For the first time, predictive marketing is accessible to all marketers, not just those at large corporations — in fact, many smaller organizations are leapfrogging their larger counterparts with innovative programs. This book shows you how to bring predictive analytics to your organization, with actionable guidance that get you started today. Implement predictive marketing at any size organization Deliver a more personalized marketing experience Automate predictive analytics with machine learning technology Base marketing decisions on concrete data rather than unproven ideas Marketers have long been talking about delivering personalized experiences across channels. All marketers want to deliver happiness, but most still employ a one-size-fits-all approach. Predictive Marketing provides the information and insight you need to lift your organization out of the campaign rut and into the rarefied atmosphere of a truly personalized customer experience.

Download or read book The SAGE Handbook of Social Media Research Methods written by Anabel Quan-Haase and published by SAGE. This book was released on 2022-09-02 with total page 860 pages. Available in PDF, EPUB and Kindle. Book excerpt: The SAGE Handbook of Social Media Research Methods spans the entire research process, from data collection to analysis and interpretation. This second edition has been comprehensively updated and expanded, from 39 to 49 chapters. In addition to a new section of chapters focussing on ethics, privacy and the politics of social media data, the new edition provides broader coverage of topics such as: Data sources Scraping and spidering data Locative data, video data and linked data Platform-specific analysis Analytical tools Critical social media analysis Written by leading scholars from across the globe, the chapters provide a mix of theoretical and applied assessments of topics, and include a range of new case studies and data sets that exemplify the methodological approaches. This Handbook is an essential resource for any researcher or postgraduate student embarking on a social media research project. PART 1: Conceptualising and Designing Social Media Research PART 2: Collecting Data PART 3: Qualitative Approaches to Social Media Data PART 4: Quantitative Approaches to Social Media Data PART 5: Diverse Approaches to Social Media Data PART 6: Research & Analytical Tools PART 7: Social Media Platforms PART 8: Privacy, Ethics and Inequalities

Download or read book Social Media Analytics written by Matthew Ganis and published by IBM Press. This book was released on 2015-12-14 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transform Raw Social Media Data into Real Competitive Advantage There’s real competitive advantage buried in today’s deluge of social media data. If you know how to analyze it, you can increase your relevance to customers, establishing yourself as a trusted supplier in a cutthroat environment where consumers rely more than ever on “public opinion” about your products, services, and experiences. Social Media Analytics is the complete insider’s guide for all executives and marketing analysts who want to answer mission-critical questions and maximize the business value of their social media data. Two leaders of IBM’s pioneering Social Media Analysis Initiative offer thorough and practical coverage of the entire process: identifying the right unstructured data, analyzing it, and interpreting and acting on the knowledge you gain. Their expert guidance, practical tools, and detailed examples will help you learn more from all your social media conversations, and avoid pitfalls that can lead to costly mistakes. You’ll learn how to: Focus on the questions that social media data can realistically answer Determine which information is actually useful to you—and which isn’t Cleanse data to find and remove inaccuracies Create data models that accurately represent your data and lead to more useful answers Use historical data to validate hypotheses faster, so you don’t waste time Identify trends and use them to improve predictions Drive value “on-the-fly” from real-time/ near-real-time and ad hoc analyses Analyze text, a.k.a. “data at rest” Recognize subtle interrelationships that impact business performance Improve the accuracy of your sentiment analyses Determine eminence, and distinguish “talkers” from true influencers Optimize decisions about marketing and advertising spend Whether you’re a marketer, analyst, manager, or technologist, you’ll learn how to use social media data to compete more effectively, respond more rapidly, predict more successfully...grow profits, and keep them growing.

Download or read book Role of Social Media in Predictive Analytics written by Prabhsimran Singh and published by . This book was released on 2023-01-07 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last decade, social media has emerged as a front-runner as a communication medium that allows people to connect at a global level by breaking the geographical barrier and enabling e-participation of people through these social media platforms which act as a virtual world. Due to the above reasons, social media has become an integral part of our lives and we use these for almost everything, ranging from news, entertainment, recommendation on products, and connecting with friends and family. This obsession is so high that out of all Internet users, 75% use social media in one way or the other. People are so much attached to this virtual world that almost every day on average, one spends at least two hours on social media. Currently, there are around 2.9 billion active social media users worldwide. These active users are continuously posting messages, images, videos, etc on various social media platforms and generating tons of user-generated content (UGC).

Download or read book Fraud Analytics Using Descriptive Predictive and Social Network Techniques written by Bart Baesens and published by John Wiley & Sons. This book was released on 2015-08-17 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: Detect fraud earlier to mitigate loss and prevent cascading damage Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques is an authoritative guidebook for setting up a comprehensive fraud detection analytics solution. Early detection is a key factor in mitigating fraud damage, but it involves more specialized techniques than detecting fraud at the more advanced stages. This invaluable guide details both the theory and technical aspects of these techniques, and provides expert insight into streamlining implementation. Coverage includes data gathering, preprocessing, model building, and post-implementation, with comprehensive guidance on various learning techniques and the data types utilized by each. These techniques are effective for fraud detection across industry boundaries, including applications in insurance fraud, credit card fraud, anti-money laundering, healthcare fraud, telecommunications fraud, click fraud, tax evasion, and more, giving you a highly practical framework for fraud prevention. It is estimated that a typical organization loses about 5% of its revenue to fraud every year. More effective fraud detection is possible, and this book describes the various analytical techniques your organization must implement to put a stop to the revenue leak. Examine fraud patterns in historical data Utilize labeled, unlabeled, and networked data Detect fraud before the damage cascades Reduce losses, increase recovery, and tighten security The longer fraud is allowed to go on, the more harm it causes. It expands exponentially, sending ripples of damage throughout the organization, and becomes more and more complex to track, stop, and reverse. Fraud prevention relies on early and effective fraud detection, enabled by the techniques discussed here. Fraud Analytics Using Descriptive, Predictive, and Social Network Techniques helps you stop fraud in its tracks, and eliminate the opportunities for future occurrence.

Download or read book Python Social Media Analytics written by Siddhartha Chatterjee and published by Packt Publishing Ltd. This book was released on 2017-07-28 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Social Media Management written by Amy Van Looy and published by Springer Nature. This book was released on 2022-05-03 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the second edition of the undergraduate textbook 'Social Media Management' which extends the original edition's scope beyond the business angle. The textbook continues with the perspective of organizations - not individuals - and clarifies the impact of social media on their different departments or disciplines, while also exploring how organizations use social media to create business value. To do so, the book pursues a uniquely multi-disciplinary approach by embracing IT, marketing, HR, and many other fields. While the first edition was inspired by the rise of social media tools, the second edition is characterized by a digital economy with increasing digitalization efforts due to newly emerging technologies in Industry 4.0 and the COVID-19 pandemic. Readers will benefit from a comprehensive selection of extended topics, including strategies and business models for social media, influencer marketing, viral campaigns, social CRM, employer branding, e-recruitment, search engine optimization, social mining, sentiment analysis, crowdfunding, and legal and ethical issues. Each chapter starts with one or more teaser questions to arouse the readers’ interest, which will be clarified per topic. The second edition also provides ample self-test materials and reflection exercises.

Download or read book Digital and Social Media Marketing written by Nripendra P. Rana and published by Springer Nature. This book was released on 2019-11-11 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines issues and implications of digital and social media marketing for emerging markets. These markets necessitate substantial adaptations of developed theories and approaches employed in the Western world. The book investigates problems specific to emerging markets, while identifying new theoretical constructs and practical applications of digital marketing. It addresses topics such as electronic word of mouth (eWOM), demographic differences in digital marketing, mobile marketing, search engine advertising, among others. A radical increase in both temporal and geographical reach is empowering consumers to exert influence on brands, products, and services. Information and Communication Technologies (ICTs) and digital media are having a significant impact on the way people communicate and fulfil their socio-economic, emotional and material needs. These technologies are also being harnessed by businesses for various purposes including distribution and selling of goods, retailing of consumer services, customer relationship management, and influencing consumer behaviour by employing digital marketing practices. This book considers this, as it examines the practice and research related to digital and social media marketing.

Download or read book Prediction and Inference from Social Networks and Social Media written by Jalal Kawash and published by Springer. This book was released on 2017-03-16 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses the challenges of social network and social media analysis in terms of prediction and inference. The chapters collected here tackle these issues by proposing new analysis methods and by examining mining methods for the vast amount of social content produced. Social Networks (SNs) have become an integral part of our lives; they are used for leisure, business, government, medical, educational purposes and have attracted billions of users. The challenges that stem from this wide adoption of SNs are vast. These include generating realistic social network topologies, awareness of user activities, topic and trend generation, estimation of user attributes from their social content, and behavior detection. This text has applications to widely used platforms such as Twitter and Facebook and appeals to students, researchers, and professionals in the field.