Difference between revisions of "Spiess2026"
AndreiKorbut (talk | contribs) (Created page with "{{BibEntry |BibType=ARTICLE |Author(s)=Oliver Spiess; Martin Luginbühl; Daniel Müller-Feldmeth; |Title=CA and quantitative approaches |Editor(s)=Matthew Burdelski; Tim Greer...") |
AndreiKorbut (talk | contribs) |
||
| Line 1: | Line 1: | ||
{{BibEntry | {{BibEntry | ||
| − | |BibType= | + | |BibType=INCOLLECTION |
|Author(s)=Oliver Spiess; Martin Luginbühl; Daniel Müller-Feldmeth; | |Author(s)=Oliver Spiess; Martin Luginbühl; Daniel Müller-Feldmeth; | ||
|Title=CA and quantitative approaches | |Title=CA and quantitative approaches | ||
Latest revision as of 03:06, 31 May 2026
| Spiess2026 | |
|---|---|
| BibType | INCOLLECTION |
| Key | Spiess2026 |
| Author(s) | Oliver Spiess, Martin Luginbühl, Daniel Müller-Feldmeth |
| Title | CA and quantitative approaches |
| Editor(s) | Matthew Burdelski, Tim Greer |
| Tag(s) | EMCA |
| Publisher | Routledge |
| Year | 2026 |
| Language | English |
| City | London |
| Month | |
| Journal | |
| Volume | |
| Number | |
| Pages | 210–226 |
| URL | Link |
| DOI | 10.4324/9781032720852-15 |
| ISBN | |
| Organization | |
| Institution | |
| School | |
| Type | |
| Edition | |
| Series | |
| Howpublished | |
| Book title | The Routledge Handbook of Conversation Analysis |
| Chapter | |
Abstract
Quantifying talk-in-interaction requires a careful balance between reducing interactional complexity and attending to demonstrable participant orientations on a turn-by-turn basis. Coding interactional behavior forms the foundation of quantification and, when designed in line with the principles of conversation analysis (CA), it can take into account the sequential and interactive nature of interaction. This chapter explores the potentials and challenges involved in extending CA through corpus linguistics, experimentation, and visualizations. It argues that these approaches benefit from CA’s formal rigor in identifying and describing interactional phenomena, especially when aiming for sound operationalization. At the same time, quantitative expansions offer significant advantages for applied CA: They make it possible to test associations between interactional phenomena and exogenous variables, and they complement micro-analytical insights with broader, macro-level perspectives. This wider lens opens up opportunities for statistically assessing CA claims and exploring interactional patterns.
Notes
