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Introduction: Tracing the History of a Discipline Through Quantitative and Qualitative Analyses of Scientific Literature Read chapter Read first chapter

2018 | OriginalPaper | Chapter

10. Topic Detection: A Statistical Model and a Quali-Quantitative Method

Author : Stefano Sbalchiero

Published in: Tracing the Life Cycle of Ideas in the Humanities and Social Sciences

Publisher: Springer International Publishing

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Abstract

This chapter aims at comparing and contrasting two approaches for the automatic detection of topics in texts that show interesting similarities and differences. Among the advances that have given a new impetus and vitality to the discipline, the importance to identify topics or, in other words, the procedures that enable us to identify thematic groups within the texts seem to be relevant to meet the scholars’ needs and have been developed in different disciplines. Two approaches are compared and contrasted. The first, well-known as Latent Dirichlet Allocation, has been developed as a part of text mining statistical model mainly to classify automatically the texts of large corpora; the second, the Reinert’s methods, was developed mainly in the social sciences to managing reliably the content analysis process by bridging the gap between qualitative and quantitative text analysis. Both the procedures proved useful, but in different ways: Latent Dirichlet Allocation enabled us to classify the abstracts automatically under certain topics, while Reinert’s method was useful for identifying the internal structure of the abstracts and extracting the macro-topics that characterized them.

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previous chapter Functional Data Analysis and Knowledge-Based Systems
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Footnotes
1
I wish to thank Martin Ponweiser for his support in developing the necessary instructions in R for implementing LDA and obtaining these graphic results.
 
2
Special thanks go to Pierre Ratinaud for his support in developing the R instructions needed to recall the results produced by Iramuteq and construct the graphs from a chronological perspective.
 
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Metadata
Title
Topic Detection: A Statistical Model and a Quali-Quantitative Method
Author
Stefano Sbalchiero
Copyright Year
2018
Book
Tracing the Life Cycle of Ideas in the Humanities and Social Sciences

Print ISBN: 978-3-319-97063-9

Electronic ISBN: 978-3-319-97064-6

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-97064-6_10

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