BIG QUALIDATA: Tackling Analysis of Very Large Volumes of Qualitative Data in Social Science Research
- BIG QUALIDATA: Tackling Analysis of Very Large Volumes of Qualitative Data in Social Science Research
- Hosted by: Sociology # University of Edinburgh; Introduced by: Lynn Jamieson # University of Edinburgh; Introduced by: Ros Edwards # University of Southampton; Introduced by: Tarani Chandola # University of Manchester
- Hosted by
- Introduced by
- Date and Time
- 9th May 2016 13:00 - 9th May 2016 16:00
- Chrystal Macmillan Building - 6th Floor Common Room
Can social researchers scale up techniques of working with qualitative data and meaningfully analyse massively more text than they can possibly read? Engage with three researchers who give answers through their work using different types of software R, Leximancer and NVivo.
Join the event in Edinburgh: Staff Room 6th Floor Chrystal Macmillan Building, 15a George Square EH8 9LD or join interacting audiences watching on screen and able to ask questions in Manchester (Room 2.07, Humanities Bridgeford Street building) & Southampton (Room 58/2097, Murray Building, Highfield Campus). There will be no catering but Edinburgh CMB has a café on the ground floor and you can bring and eat your lunch. Note the event is being filmed; please tell the organiser if you wish to remain off camera.
The event is free to attend but registration is necessary. Please email email@example.com stating which venue you wish to attend.
Chairs: Lynn Jamieson, University of Edinburgh; Ros Edwards, University of Southampton and Tarani Chandola, University of Manchester
This is an NCRM research workshop http://www.ncrm.ac.uk linked to the NCRM project Working across qualitative longitudinal studies: a feasibility study looking at care and intimacy (Edwards and Weller Southampton, Jamieson and Davidson Edinburgh)
Each speaker will speak for 30 minutes followed by fifteen minutes taking immediate questions. The workshop will conclude with open discussion.
1.0 Welcome Lynn Jamieson
1.10-1.40 Using R in analysis of news media and political discourse, Professor Benoit
Professor Ken Benoit, Professor of Political Science Research Methodology, LSE, is the Principal Investigator in an ERC funded project QUANTESS developing innovative methods for the quantitative analysis of textual data in the social sciences. He is the co-author with Paul Nulty of the R software package for text analysis “quanteda”, and working on a book Quantitative Text Analysis Using R covering methods for managing, processing, and analysing textual data using the R programming language. He has taught quantitative text analysis extensively and has published research in this area targeting both methodology and political science applications.
1.55- 2.25 Using Leximancer to analyse written feedback from the Postgraduate Taught Experience Survey (feedback from students in 100 Higher Education Institutions).
Dr Elena Zaitseva, Teaching and Learning Academy, Liverpool John Moores University has been using semantic analysis software Leximancer for analysis of large text-based data sets since 2011. Outcomes of this research are published in the Quality in Higher Education Journal, several book chapters and in two reports commissioned by the Higher Education Academy including: Zaitseva, E. and C. Milsom (2016), In their own words: Analysing students’ comments from the Postgraduate Taught Experience Survey. Report, York: Higher Education Academy. Available from: https://www.heacademy.ac.uk/resource/their-own-words
2.40-3.10 Keyness and Discourse Intertextuality in Qualitative and Mixed Methods Research (Using NVivo with the British National Corpus)
Professor Wendy Olsen, Professor of Socio-Economics, Manchester University, with Samantha Watson and John McLoughlin: ‘The need for a dispassionate approach to analysing mixed methods data led me to using NVIVO in combination with the British National Corpus. The latter covers varied uses of English, and we examine the prevalence of words in our own Qualitative Corpus versus the BNC. I create NVIVO nodes for each highly prevalent 'keyword' based on Touri and Koteyko (IJSRM, 18:6, 2015). Next I conduct discourse analysis by seeing how groups of these words are used together to achieve intended meanings. Using NVIVO matrix queries, I discover the extent of intertextuality for each pair of discourses. The method offers rigour, sophistication and transparency.’