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Tracing the life cycle of ideas in the humanities and social sciences

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Tracing the life cycle of ideas in the humanities and social sciencesedited by Arjuna Tuzzi.
其他作者:	Tuzzi, Arjuna.
出版者:	Cham :Springer International Publishing :2018.
面頁冊數:	xii, 217 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	HumanitiesResearch.
電子資源:	https://doi.org/10.1007/978-3-319-97064-6
ISBN:	9783319970646$q(electronic bk.)

Tracing the life cycle of ideas in the humanities and social sciences
Tracing the life cycle of ideas in the humanities and social sciences[electronic resource] /edited by Arjuna Tuzzi. - Cham :Springer International Publishing :2018. - xii, 217 p. :ill., digital ;24 cm. - Quantitative methods in the humanities and social sciences,2199-0956. - Quantitative methods in the humanities and social sciences..

Chapter 1. Introduction. Tracing the History of a Discipline through Quantitative and Qualitative Analyses of Scientific Literature -- Chapter 2. Tracing the Words of the Analytic Turn in the Journal of Philosophy -- Chapter 3. Exploring the History of American Sociology through Topic Modelling -- Chapter 4. Histories of Social Psychology in Europe and North America, as Seen from Research Topics in Two Key Journals -- Chapter 5. First Steps in Shaping the History of Linguistics in Italy: The Archivio Glottologico Italiano -- Chapter 6. The Modern History of Statistics: Comparing Temporal Patterns of Word Clusters -- Chapter 7. Treat Texts as Data but Remember They Are Made of Words: Compiling and Pre-processing Corpora -- Chapter 8. Automatic Multiword Identification in a Specialist Corpus -- Chapter 9. Functional Data Analysis and Knowledge-Based Systems -- Chapter 10. Topic Detection. A Statistical Model and a Quali-quantitative Method -- Chapter 11. What Have We Learnt? Some Concluding Remarks.

This book demonstrates how quantitative methods for text analysis can successfully combine with qualitative methods in the study of different disciplines of the Humanities and Social Sciences (HSS) The book focuses on learning about the evolution of ideas of HSS disciplines through a distant reading of the contents conveyed by scientific literature, in order to retrieve the most relevant topics being debated over time. Quantitative methods, statistical techniques and software packages are used to identify and study the main subject matters of a discipline from raw textual data, both in the past and today. The book also deals with the concept of quality of life of words and aims to foster a discussion about the life cycle of scientific ideas. Textual data retrieved from large corpora pose interesting challenges for any data analysis method and today represent a growing area of research in many fields. New problems emerge from the growing availability of large databases and new methods are needed to retrieve significant information from those large information sources. This book can be used to explain how quantitative methods can be part of the research instrumentation and the "toolbox" of scholars of Humanities and Social Sciences. The book contains numerous examples and a description of the main methods in use, with references to literature and available software. Most of the chapters of the book have been written in a non-technical language for HSS researchers without mathematical, computer or statistical backgrounds.

ISBN: 9783319970646$q(electronic bk.)

Standard No.: 10.1007/978-3-319-97064-6doiSubjects--Topical Terms:

541227
Humanities
--Research.

LC Class. No.: H62 / .T733 2018

Dewey Class. No.: 300.72

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505 0 $a Chapter 1. Introduction. Tracing the History of a Discipline through Quantitative and Qualitative Analyses of Scientific Literature -- Chapter 2. Tracing the Words of the Analytic Turn in the Journal of Philosophy -- Chapter 3. Exploring the History of American Sociology through Topic Modelling -- Chapter 4. Histories of Social Psychology in Europe and North America, as Seen from Research Topics in Two Key Journals -- Chapter 5. First Steps in Shaping the History of Linguistics in Italy: The Archivio Glottologico Italiano -- Chapter 6. The Modern History of Statistics: Comparing Temporal Patterns of Word Clusters -- Chapter 7. Treat Texts as Data but Remember They Are Made of Words: Compiling and Pre-processing Corpora -- Chapter 8. Automatic Multiword Identification in a Specialist Corpus -- Chapter 9. Functional Data Analysis and Knowledge-Based Systems -- Chapter 10. Topic Detection. A Statistical Model and a Quali-quantitative Method -- Chapter 11. What Have We Learnt? Some Concluding Remarks.
520 $a This book demonstrates how quantitative methods for text analysis can successfully combine with qualitative methods in the study of different disciplines of the Humanities and Social Sciences (HSS) The book focuses on learning about the evolution of ideas of HSS disciplines through a distant reading of the contents conveyed by scientific literature, in order to retrieve the most relevant topics being debated over time. Quantitative methods, statistical techniques and software packages are used to identify and study the main subject matters of a discipline from raw textual data, both in the past and today. The book also deals with the concept of quality of life of words and aims to foster a discussion about the life cycle of scientific ideas. Textual data retrieved from large corpora pose interesting challenges for any data analysis method and today represent a growing area of research in many fields. New problems emerge from the growing availability of large databases and new methods are needed to retrieve significant information from those large information sources. This book can be used to explain how quantitative methods can be part of the research instrumentation and the "toolbox" of scholars of Humanities and Social Sciences. The book contains numerous examples and a description of the main methods in use, with references to literature and available software. Most of the chapters of the book have been written in a non-technical language for HSS researchers without mathematical, computer or statistical backgrounds.
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