Discussing the planning and testing phase of data analysis tools upgrades.
This is the findings from running three analysis on a same data set - one manual, one rule-based and one machine-learning based to summarize unstructured research data.
I discuss an example of a project where I used semantic analysis to humanize data during research analysis.
We discuss three challenges in reconciling structured and unstructured data in research analysis.
We discuss the process of building custom dictionaries for research and three limitations of commercial dictionaries.
What might be an interesting construct for automating the processing of some of your participant research? We look at semantic automation.
Today we talk about the opportunities and contributions of the academic field to our research work.
What should we think about when paying for participants? How can payment skew the research work?
This is a ten minutes segment from a one-hour interview with guest Charlie Beckett, past senior producer and programme editor at BBC News and Current affairs, current founding director of Polis, the think-tank for research and debate around international journalism and society (London School of Economics). You can find the original podcast episode here: Different by Design.
Tips and thoughts for your first round of interviews in the healthcare field. --- Send in a voice message: https://podcasters.spotify.com/pod/show/corina-paraschiv65/message
UPDATED - This is Part of the Data Stories Series Written by Corina Paraschiv. A special thank you to Kenneth D. Bailey’s work on typologies and taxonomies, for having inspired this Data Story.
A reflection on the value of self-referential coding in informing your research - when handled cautiously.
During COVID, we had to rethink how to design the end-to-end experience for co-creation workshops, for the digital realm. Inspired by Ian Chipchase’s reflections on characteristics of popup studios, here is how we digitalized our workshop spaces for participants.
I share an example from a project around wayfinding and people with autism, as a springboard to rethinking inclusive research protocoles.
How do we maintain objectivity and remove bias, while also accommodating research participants? A short reflection.
This is Part of the Data Stories Series. Written by Corina Paraschiv A special thank you to Kenneth D. Bailey’s work on typologies and taxonomies, for having inspired this Data Story.
Learning the programming language R can be done through two approaches. Which one makes the most sense for researchers?
Researchers use categories all the time. While embracing diversity and plurality, researchers nevertheless often resort to classifications and groupings. Why are categorizations so important? What role do they fulfill in our roles as researchers? This episode is part of the Data Stories Series, and you can find a written version of it on Medium, here.
A few sources to investigate further, for this episode: Elizabeth Weil's article. Linguist Noam Chomsky at the AI Summit, Wolfram's Q&A on Chat GPT. --- Send in a voice message: https://anchor.fm/corina-paraschiv65/message
Frequency measures are common in qualitative and quantitative data analysis. But are they always informative? Can they be false friends? Here are three ideas around better use of frequency measures in your user research.