Map Causality in Qualitative Data with CausalMap
In this webinar, the Causal Map team will introduce you to causal mapping, a way to find out about people’s mental models of the world: what they think causes what, based on interview transcripts or other documents. We will show you that Causal Map does what no other software can: it enables you to directly code, organise, consolidate and understand the causal claims contained within narrative information and present the results as a variety of compelling graphics which we call “maps”.
How to code, analyse and visualise qualitative information about causal connections with Causal Map
Jaimie was carrying out research on social capital in Mali. She wanted to know what kind of contribution informal tea clubs might make to different aspects social capital, and via what pathways or mechanisms. She used Causal Map to code her interview transcripts using causal Qualitative Data Analysis and generate causal maps to visualise the causal pathways. It worked great, and her paper is currently in the “revise and resubmit” stage.
About the Tool
Causal mapping has been used since 1976 in areas from ecology to business management. It is a rigorous, qualitative research approach which helps researchers quickly cut to the chase in answering some of the most important research questions: what causes what, in the minds of key stakeholders? The Causal Map web app (which is free to use for small studies) is a new way to make causal mapping more accessible to researchers.
About Authors
Steve Powell - Co-founder and Director
Steve has led and contributed to research and evaluation projects in many countries around the world over the last 25 years. He has worked on a wide range of topics, from psychosocial programming after the 2004 tsunami and community resilience in East Africa to counting stray dogs in Sarajevo. Steve has expertise in both quantitative and qualitative research and evaluation approaches. He gained his PhD in psychology researching post-traumatic stress after the war in Bosnia-Herzegovina.
This research and evaluation work left Steve longing for a better way to collect and synthesise people’s ideas about ‘what influences what’. This inspired Steve to co-found Causal Map Ltd.
Fiona Remnant - Co-founder and Director
Fiona is a communications and research professional, with a special interest in the practical application of academic research in the international development sector. She has worked in communications in the private and NGO sector, in both regional and international roles.
Fiona was co-author of the Qualitative Impact Protocol (QuIP) whilst working at the Centre for Development Studies at the University of Bath, and founded Bath Social and Development Research (Bath SDR) Ltd in 2016 to promote more and better use of the QuIP.
Hannah Mishan - Outreach Specialist
Hannah is a project manager at Bath SDR, who works with Steve to improve educational materials and support users of the app. She also works to promote use and understanding of the tool through the creation of online content.
Hannah has previously held communications and outreach roles in the charity sector and brings this experience to her role with Casual Map. They studied International Development at both undergraduate and Masters level with a particular interest in sustainability. Throughout this time she became increasingly interested in the theories and tools surrounding qualitative data analysis.
Other Resources
The causalmap.app website, where you can sign up for updates and use code SAGECM23 to get a 50% discount.
A more in-depth demo of Causal Map
Q&A
+ Is Causal Map free or do you need a subscription?
There are free and paid for versions for the app, you can find more information on the website. You can also use the code SAGECM23 to get 50% off when you sign up.
+ Could you recommend readings/literature for those of us starting out with qualitative causal maps?
You can find a few resources including a zotero library here
+ Are there more details about the study you talk about in the tutorial?
You can find more information about this study here.
+ Have you used Causal Map with social media data?
Yes, it is possible to use Causal Map with social media data, you can simply import it and code it. With Twitter data, consider whether you can realistically identify causal relationships in the text - this will work better if you select your hashtags carefully. We would not recommend coding tens of thousands of tweets with Causal Map as that would be very labour-intensive.
+ How does Causal Map compare with other qualitative data analysis tools like Atlas.ti and NVIVO?
There are a lot of excellent qualitative data analysis tools that can be used for a variety of techniques. Causal Map specifically addresses causal connections and simplifies the job of a researcher to code these. We are not aware of other qualitative data analysis tools that can do this without additional effort. Of course there may be and we might not have come across them.
+ Is it easy to use Causal Map to construct tables for qualitative data compared to manually doing it?
We used Excel to create manual links for a few years - it’s possible, but it’s much harder and slower, and you don’t have the benefit of the algorithms to help with the more sophisticated analysis.
+ Can I import already coded data?
Yes you can. You can upload both the links and the relevant statements (with the highlighted coded claim).
+ Can I use text files?
Yes, you can directly upload text files including docx files for coding.
+ Can I delete the data I uploaded?
You can delete the data or file from your dashboard.
+ What about data privacy?
It is generally recommended that any qualitative data that requires anonymisation is anonymised before analysis, so we would expect anyone using Causal Map to have done that in advance. In terms of storage, all data is encrypted and we use Amazon cloud locations in Europe.
+ Could we use the source count to essentially argue the strength of causation?
There is a place for both qualitative and quantitative analysis when evaluating causal relationships. With Causal Map we are aiming to help researchers understand and describe and even count the causal links that the groups they are studying make. But we would not use source count as a proxy for the strength of the relationship.
+ Are there any papers using Causal Map for their analysis?
There are plenty of research reports which used Causal Map. Academic papers are still in the pipeline, watch this space. Here is a preprint.
