Introduction to Text Analytics

A Guide for Digital Humanities & Social Sciences

AvEmily Öhman

Häftad, Engelska, 2024

496 kr

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Beskrivning

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.

Produktinformation

Utgivningsdatum:2024-12-02
Mått:170 x 242 x 24 mm
Vikt:570 g
Format:Häftad
Språk:Engelska
Antal sidor:360
Upplaga:1
Förlag:SAGE Publications
ISBN:9781529620047

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Referensverk och tvärvetenskap inom Samhälle och politik

Mer om författaren

Dr. Emily Öhman 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.

Innehållsförteckning

Basic Concepts and Tools for Text AnalyticsChapter 1: Computational and Traditional Text AnalysisChapter 2: Basic Tools for Text AnalyticsChapter 3: Dataset Creation and ConsiderationsLanguage and ComputersChapter 4: Language and ComputersChapter 5: Regular ExpressionsProgramming for Text AnalyticsChapter 6: Introduction to Python ProgrammingChapter 7: Pre-processing Textual DataChapter 8: Data Manipulation and ExplorationChapter 9: Data VisualizationSocial Media AnalyticsChapter 10: Text MiningChapter 11: Social Media AnalysisChapter 12: The Basics of Machine LearningPublishingChapter 13: LaTex Basics