Attributing Authorship
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Attributing Authorship
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Author : Harold Love
language : en
Publisher: Cambridge University Press
Release Date : 2002-06-20
Attributing Authorship written by Harold Love and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-06-20 with Language Arts & Disciplines categories.
Recent literary scholarship has seen a shift of interest away from questions of attribution. Yet these questions remain urgent and important for any historical study of writing, and have been given a powerful new impetus by advances in statistical studies of language and the coming on line of large databases of texts in machine-searchable form. The present book is the first comprehensive survey of the field from a literary perspective to appear for forty years. It covers both traditional and computer based approaches to attribution, and evaluates each in respect of their potentialities and limitations. It revisits a number of famous controversies, including those concerning the authorship of the Homeric poems, books from the Old and New Testaments, and the plays of Shakespeare. Written with wit as well as erudition Attributing Authorship will make this intriguing field accessible for students and scholars alike.
Authorship Attribution
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Author : Patrick Juola
language : en
Publisher: Now Publishers Inc
Release Date : 2008
Authorship Attribution written by Patrick Juola and has been published by Now Publishers Inc this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Computers categories.
Authorship Attribution surveys the history and present state of the discipline, presenting some comparative results where available. It also provides a theoretical and empirically-tested basis for further work. Many modern techniques are described and evaluated, along with some insights for application for novices and experts alike.
Social Network Analytics For Contemporary Business Organizations
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Author : Himani Bansal
language : en
Publisher: Business Science Reference
Release Date : 2018
Social Network Analytics For Contemporary Business Organizations written by Himani Bansal and has been published by Business Science Reference this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Business & Economics categories.
Social technology is quickly becoming a vital tool in our personal, educational, and professional lives. Its use must be further examined in order to determine the role of social media technology in organizational settings to promote business development and growth. Social Network Analytics for Contemporary Business Organizations is a critical scholarly resource that analyzes the application of social media in business applications. Featuring coverage on a broad range of topics, such as business management, dynamic networks, and online interaction, this book is geared towards professionals, researchers, academics, students, managers, and practitioners actively involved in the business industry.
Authorship Attribution In Turkish Texts
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Author : Hülya Kocagül Yüzer
language : en
Publisher: Artsürem
Release Date : 2022-12-31
Authorship Attribution In Turkish Texts written by Hülya Kocagül Yüzer and has been published by Artsürem this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-31 with Language Arts & Disciplines categories.
The latest developments in the field of computer technology have created new ways to share information without time and space limits. Computer technologies have not only made life easier and more accessible for users, but they have also opened up a new arena for illegal activities. These illegal actions have found an opportunity to spread via e-mails, websites, Internet chat rooms, forum pages, and social networking websites (like Facebook, Twitter, Instagram). Online contributors do not need to provide information such as their real names, the city where they live, age or gender in order to share their opinions, and such feelings of anonymity encourage criminal activities. Thus, disputed authorship cases have become one of the main challenges of the technological era. This research is a corpus-based simulated authorship casework application in Turkish. Texts for the corpora were collected from a collaborative online encyclopaedia – Eksi Sozluk (Sour Times) and Twitter. The corpus consists of 900 texts from 52 authors in total. However, 105 texts belong to seven authors from Twitter. The two methodological approaches that were applied are qualitative and statistical methods, according to Grant’s (2013) approach. Ten different tests were applied, depending on the various parameters that are forensically possible in real-world cases. Accordingly, the role of feature type, size, including the candidate author size, text size and a limited number of texts per author and finally cross-genre application were tested. The analyses revealed that such a combined approach has promising results in some tests in that they attributed authorship in Turkish. The findings of the research indicated that there is the potential to attribute unknown authors in Turkish and it appears that the results have significant conclusions for the broader application of forensic authorship attribution techniques in Turkish texts. Keywords: Authorship Attribution, Turkish, Forensic Linguistics, Authorship Analysis
Scalability Issues In Authorship Attribution
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Author : Kim Luyckx
language : en
Publisher: ASP / VUBPRESS / UPA
Release Date : 2011-08
Scalability Issues In Authorship Attribution written by Kim Luyckx and has been published by ASP / VUBPRESS / UPA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-08 with Computers categories.
Provides an in-depth and systematic study of the so-called scalability issues in authorship attribution -- the task that aims to identify the author of a text, given a model of authorial style based on texts of known authorship. Computational authorship attribution does not rely on in-depth reading, but rather automates the process. This book investigates the behavior of a text categorization approach to the task when confronted with scalability issues. By addressing the issues of experimental design, data size, and author set size, the dissertation demonstrates whether the approach taken is valid in experiments with limited or sufficient data, and with small or large sets of authors.
Machine Learning Methods For Stylometry
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Author : Jacques Savoy
language : en
Publisher: Springer
Release Date : 2020-11-23
Machine Learning Methods For Stylometry written by Jacques Savoy and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-23 with Computers categories.
This book presents methods and approaches used to identify the true author of a doubtful document or text excerpt. It provides a broad introduction to all text categorization problems (like authorship attribution, psychological traits of the author, detecting fake news, etc.) grounded in stylistic features. Specifically, machine learning models as valuable tools for verifying hypotheses or revealing significant patterns hidden in datasets are presented in detail. Stylometry is a multi-disciplinary field combining linguistics with both statistics and computer science. The content is divided into three parts. The first, which consists of the first three chapters, offers a general introduction to stylometry, its potential applications and limitations. Further, it introduces the ongoing example used to illustrate the concepts discussed throughout the remainder of the book. The four chapters of the second part are more devoted to computer science with a focus on machine learning models. Their main aim is to explain machine learning models for solving stylometric problems. Several general strategies used to identify, extract, select, and represent stylistic markers are explained. As deep learning represents an active field of research, information on neural network models and word embeddings applied to stylometry is provided, as well as a general introduction to the deep learning approach to solving stylometric questions. In turn, the third part illustrates the application of the previously discussed approaches in real cases: an authorship attribution problem, seeking to discover the secret hand behind the nom de plume Elena Ferrante, an Italian writer known worldwide for her My Brilliant Friend’s saga; author profiling in order to identify whether a set of tweets were generated by a bot or a human being and in this second case, whether it is a man or a woman; and an exploration of stylistic variations over time using US political speeches covering a period of ca. 230 years. A solutions-based approach is adopted throughout the book, and explanations are supported by examples written in R. To complement the main content and discussions on stylometric models and techniques, examples and datasets are freely available at the author’s Github website.
The Author
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Author : Andrew Bennett
language : en
Publisher: Routledge
Release Date : 2004-12-24
The Author written by Andrew Bennett and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-12-24 with Literary Criticism categories.
This volume investigates the changing definitions of the author, what it has meant historically to be an 'author', and the impact that this has had on literary culture. Andrew Bennett presents a clearly-structured discussion of the various theoretical debates surrounding authorship, exploring such concepts as authority, ownership, originality, and the 'death' of the author. Accessible, yet stimulating, this study offers the ideal introduction to a core notion in critical theory.
Python Real World Data Science
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Author : Dusty Phillips
language : en
Publisher: Packt Publishing Ltd
Release Date : 2016-06-10
Python Real World Data Science written by Dusty Phillips and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-10 with Computers categories.
Unleash the power of Python and its robust data science capabilities About This Book Unleash the power of Python 3 objects Learn to use powerful Python libraries for effective data processing and analysis Harness the power of Python to analyze data and create insightful predictive models Unlock deeper insights into machine learning with this vital guide to cutting-edge predictive analytics Who This Book Is For Entry-level analysts who want to enter in the data science world will find this course very useful to get themselves acquainted with Python's data science capabilities for doing real-world data analysis. What You Will Learn Install and setup Python Implement objects in Python by creating classes and defining methods Get acquainted with NumPy to use it with arrays and array-oriented computing in data analysis Create effective visualizations for presenting your data using Matplotlib Process and analyze data using the time series capabilities of pandas Interact with different kind of database systems, such as file, disk format, Mongo, and Redis Apply data mining concepts to real-world problems Compute on big data, including real-time data from the Internet Explore how to use different machine learning models to ask different questions of your data In Detail The Python: Real-World Data Science course will take you on a journey to become an efficient data science practitioner by thoroughly understanding the key concepts of Python. This learning path is divided into four modules and each module are a mini course in their own right, and as you complete each one, you'll have gained key skills and be ready for the material in the next module. The course begins with getting your Python fundamentals nailed down. After getting familiar with Python core concepts, it's time that you dive into the field of data science. In the second module, you'll learn how to perform data analysis using Python in a practical and example-driven way. The third module will teach you how to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis to more complex data types including text, images, and graphs. Machine learning and predictive analytics have become the most important approaches to uncover data gold mines. In the final module, we'll discuss the necessary details regarding machine learning concepts, offering intuitive yet informative explanations on how machine learning algorithms work, how to use them, and most importantly, how to avoid the common pitfalls. Style and approach This course includes all the resources that will help you jump into the data science field with Python and learn how to make sense of data. The aim is to create a smooth learning path that will teach you how to get started with powerful Python libraries and perform various data science techniques in depth.
Forensic Linguistics
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Author : Kanti Shukla
language : en
Publisher: Educohack Press
Release Date : 2025-01-07
Forensic Linguistics written by Kanti Shukla and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-07 with Law categories.
"Forensic Linguistics: Solving Crimes with Language" provides an in-depth look at how language plays a crucial role in solving crimes. We start by exploring forensic linguistics, explaining complex concepts in a simple and accessible way. This book aims to answer all your questions about forensic evidence, making it a valuable resource. In the second half of the book, we delve into crime scene investigation, detailing the processes that police officials follow to gather valuable evidence. This section offers an informative insight into the inner workings of crime scene investigations. Our goal is to make complex topics easy to understand, providing all the necessary knowledge without wasting readers' time. This book is especially useful for students and anyone interested in the field of forensic linguistics and crime investigation.
10 Machine Learning Blueprints You Should Know For Cybersecurity
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Author : Rajvardhan Oak
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-05-31
10 Machine Learning Blueprints You Should Know For Cybersecurity written by Rajvardhan Oak and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-31 with Computers categories.
Work on 10 practical projects, each with a blueprint for a different machine learning technique, and apply them in the real world to fight against cybercrime Purchase of the print or Kindle book includes a free PDF eBook Key Features Learn how to frame a cyber security problem as a machine learning problem Examine your model for robustness against adversarial machine learning Build your portfolio, enhance your resume, and ace interviews to become a cybersecurity data scientist Book Description Machine learning in security is harder than other domains because of the changing nature and abilities of adversaries, high stakes, and a lack of ground-truth data. This book will prepare machine learning practitioners to effectively handle tasks in the challenging yet exciting cybersecurity space. The book begins by helping you understand how advanced ML algorithms work and shows you practical examples of how they can be applied to security-specific problems with Python – by using open source datasets or instructing you to create your own. In one exercise, you'll also use GPT 3.5, the secret sauce behind ChatGPT, to generate an artificial dataset of fabricated news. Later, you'll find out how to apply the expert knowledge and human-in-the-loop decision-making that is necessary in the cybersecurity space. This book is designed to address the lack of proper resources available for individuals interested in transitioning into a data scientist role in cybersecurity. It concludes with case studies, interview questions, and blueprints for four projects that you can use to enhance your portfolio. By the end of this book, you'll be able to apply machine learning algorithms to detect malware, fake news, deep fakes, and more, along with implementing privacy-preserving machine learning techniques such as differentially private ML. What you will learn Use GNNs to build feature-rich graphs for bot detection and engineer graph-powered embeddings and features Discover how to apply ML techniques in the cybersecurity domain Apply state-of-the-art algorithms such as transformers and GNNs to solve security-related issues Leverage ML to solve modern security issues such as deep fake detection, machine-generated text identification, and stylometric analysis Apply privacy-preserving ML techniques and use differential privacy to protect user data while training ML models Build your own portfolio with end-to-end ML projects for cybersecurity Who this book is for This book is for machine learning practitioners interested in applying their skills to solve cybersecurity issues. Cybersecurity workers looking to leverage ML methods will also find this book useful. An understanding of the fundamental machine learning concepts and beginner-level knowledge of Python programming are needed to grasp the concepts in this book. Whether you're a beginner or an experienced professional, this book offers a unique and valuable learning experience that'll help you develop the skills needed to protect your network and data against the ever-evolving threat landscape.