Text Analytics for corpus linguistics and digital humanities simple r scripts and tools
List of FiguresList of TablesAcknowledgements1. Introduction2. Spikes of Frequencies and First Steps in UNIX3. Frequency Lists and First Steps in R4. Overuse and Keywords and Using R Libraries5. Document Classification and Supervised ML in LightSide and R6. Topic Modelling and Unsupervised ML with M...
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| 1. Verfasser: | |
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| Format: | UnknownFormat |
| Sprache: | eng |
| Veröffentlicht: |
London, New York, Oxford, New Dehli, Sydney
Bloomsbury Academic
2024
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| Schlagworte: |
Text data mining
> R (Computer program language)
> Corpora (Linguistics)
> Data processing
> Digital humanities
> Research
> COMPUTERS / Natural Language Processing
> COMPUTERS / Programming Languages / General
> Computational linguistics
> Computerlinguistik und Korpuslinguistik
> Data analysis: general
> Datenwissenschaft und -analyse: allgemein
> LANGUAGE ARTS & DISCIPLINES / Library & Information Science
> Programmier- und Skriptsprachen, allgemein
> Programming & scripting languages: general
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| Online Zugang: | Cover |
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| Zusammenfassung: | List of FiguresList of TablesAcknowledgements1. Introduction2. Spikes of Frequencies and First Steps in UNIX3. Frequency Lists and First Steps in R4. Overuse and Keywords and Using R Libraries5. Document Classification and Supervised ML in LightSide and R6. Topic Modelling and Unsupervised ML with Mallet and R7. Kernel Density Estimation for Conceptual Maps8. Distributional Semantics9. BERT Models10. ConclusionsReferencesIndex Do you want to gain a deeper understanding of how big tech analyzes and exploits our text data, or investigate how political parties differ by analyzing textual styles, associations and trends in documents? Or create a map of a text collection and write a simple QA system yourself? This open access book explores how to apply state-of-the-art text analytics methods to detect and visualize phenomena in text data. Solidly based on methods from corpus linguistics, natural language processing, text analytics and digital humanities, this book shows readers how to conduct experiments with their own corpora and research questions, underpin their theories, quantify the differences and pinpoint characteristics. Case studies and experiments are detailed in every chapter using real-world and open access corpora from politics, World English, history, and literature. The results are interpreted and put into perspective, pitfalls are pointed out, and necessary pre-processing steps are demonstrated. This book also demonstrates how to use the programming language R, as well as simple alternatives and additions to R, to conduct experiments and employ visualisations by example, with extensible R-code, recipes, links to corpora, and a wide range of methods. The methods introduced can be used across texts of all disciplines, from history or literature to party manifestos and patient reports.The ebook editions of this book are available open access under a CC BY-NC-ND 4.0 licence on bloomsburycollections.com |
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| Beschreibung: | ix, 224 Seiten Illustrationen, Diagramme |
| ISBN: | 1350370827 1-350-37082-7 9781350370821 978-1-350-37082-1 |