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9781529620047 Academic Inspection Copy

Introduction to Text Analytics

A Guide for Digital Humanities & Social Sciences
  • ISBN-13: 9781529620047
  • Publisher: SAGE PUBLICATIONS LTD
    Imprint: SAGE PUBLICATIONS LTD
  • By Emily Ahman
  • Price: AUD $90.99
  • Stock: 0 in stock
  • Availability: This book is temporarily out of stock, order will be despatched as soon as fresh stock is received.
  • Local release date: 14/12/2024
  • Format: Paperback (246.00mm X 184.00mm) 344 pages Weight: 0g
  • Categories: Research methods: general [GPS]
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This easy-to-follow book will revolutionise how you approach text mining and data analysis as well as equipping you with the tools, and confidence, to navigate complex qualitative data. It can be challenging to effectively combine theoretical concepts with practical, real-world applications but this accessible guide provides you with a clear step-by-step approach. Written specifically for students and early career researchers this pragmatic manual will: * Contextualise your learning with real-world data and engaging case studies. * Encourage the application of your new skills with reflective questions. * Enhance your ability to be critical, and reflective, when dealing with imperfect data. Supported by practical online resources, this book is the perfect companion for those looking to gain confidence and independence whilst using transferable data skills.
Dr. Emily OEhman is an Assistant Professor of Digital Humanities at Waseda University, Japan, where she bridges the gap between computational techniques and humanities research. Awarded her PhD in Language Technology from the University of Helsinki in 2021, she has since carved a niche for herself in the realms of sentiment analysis and emotion detection, particularly within narrative texts. Her work, which employs natural language processing (NLP) methods, spans a multitude of interdisciplinary projects, from computational literary studies to political science, and social media and communication studies analysis.
Basic Concepts and Tools for Text Analytics Chapter 1: Computational and Traditional Text Analysis Chapter 2: Basic Tools for Text Analytics Chapter 3: Dataset Creation and Considerations Language and Computers Chapter 4: Language and Computers Chapter 5: Regular Expressions Programming for Text Analytics Chapter 6: Introduction to Python Programming Chapter 7: Pre-processing Textual Data Chapter 8: Data Manipulation and Exploration Chapter 9: Data Visualization Social Media Analytics Chapter 10: Text Mining Chapter 11: Social Media Analysis Chapter 12: The Basics of Machine Learning Publishing Chapter 13: LaTex Basics
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