Computational text analysis and ‘big qual’ data

Title
Computational text analysis and ‘big qual’ data
Speaker(s)
Speaker: Emma Davidson # University of Edinburgh; Speaker: Lynne Jamieson # University of Edinburgh; Speaker: Justin Ho # University of Edinburgh
Hosted by
Introduced by
Date and Time
30th Nov 2017 13:00 - 30th Nov 2017 14:15
Location
Practice Suite 1.12, Chrystal Macmillan Building
URL
http://www.sps.ed.ac.uk/q-step/community/events/research_seminars/2017/computational_text_analysis_and_big_qual_data

How feasible is it to conduct secondary data analysis across large volumes of qualitative data from different projects? And how can this be practiced with qualitative integrity? In this seminar, Emma Davidson, Lynne Jamieson and Justin Ho will explore these questions, drawing on their experiences of ‘Working Across Qualitative Longitudinal Studies: a feasibility study looking at care and intimacy’. The aim of the project is to develop secondary analytic practice for working with ‘big qual’ data, to produce analyses that work horizontally and vertically. Part of the project has involved examining the possibilities and pitfalls of applying computational textual analysis to large volumes of qualitative data. In this seminar, the three will focus specifically on their analysis using R, and their approach to bringing computational analysis into conversation with in-depth qualitative insights.

This event will take place on Thursday, November 30 from 1pm-2.15pm in the Practice Suite (1.12) on the 1st floor of the Chrystal Macmillan Building.

Students laughing