From Text Networks to Narrative Actor Networks
Published online by Cambridge University Press: 05 July 2014
Introduction
The combined use of quantitative and qualitative methods is almost as old as sociological research, but this combination has only recently come to the forefront of the methodological debate. This is shown by the large number of reference works advocating a high level of methodological integration (Tashakkori and Teddlie 1998, 2003; Creswell 2003; Brewer and Hunter 2006; Creswell and Plano Clark 2007; Bergman 2008) that have been published since the late 1990s. However, works of this type have often limited their focus to the stage of gathering data. The methodological literature is fairly lacking in presenting and discussing strategies of analysis in which the data analysis is neither strictly quantitative (mathematical) nor strictly qualitative (interpretive). This chapter presents and discusses one example of this kind of analysis as applied to narrative interviews.
More precisely, this chapter presents an analysis procedure in which, from information obtained through qualitative techniques (narrative-biographical interviews) matrices of relations between actors are drawn up and analyzed using standard (quantitative) procedures of social network analysis. It is important to note that this transformation of narrative information from the interviews into a matrix of quantified data is preceded by a preliminary stage in which an interpretively generated code takes into account the syntactic and semantic nature of the text of the interviews. This strategy prevents loss of information about the content of the texts and respects the articulation of the textual units. The second stage, of transforming the already interpreted qualitative data to matrix form and submitting them to the corresponding algebra, can be described, in mixed methods terminology, as a “quantitizing strategy” (Tashakkori and Teddlie 1998:126; Onwuegbuzie and Teddlie 2003:355) or a “quantitative translation” (Boyatzis 1998:129). The particularity of our analysis lies in the fact that the quantitative data obtained are of a relational rather than a purely statistical-attributive nature.
To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Find out more about the Kindle Personal Document Service.
To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.
To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.