I first heard the term methodological playground in 2014, from Institute for Education’s Professor Carey Jewitt. She was talking about her work with digital artists and social researchers, synthesizing methods to open up different perspectives, generate imaginative research questions, and create a wider range of research tools. Around that time I was working on an…
Next month will be two years since my first post. Back then examples of big data in social research and evaluation were more limited and the courses on offer were not so specialised for a social research audience. Things are different today. 1) A wider range of social research methods courses connected to big data,…
In my last post I talked about why I chose to pursue R via DataCamp. Between January and the end of March I completed the first three courses of the data analyst with R track. I found a rhythm for learning in limited time – structured exercises through the DataCamp course, daily practice to recap…
An upsurge in paid work meant professional development took a back seat for a while. In this post I talk about finding a realistic way forward for developing my data skills, within a limited amount of time. In my last post, ten months ago, I described lessons learned from dipping into different software and programming…
In this blog I will share what I have learned from sitting at my desk trying to install and use new software and code. The aim is to help you get started and, more importantly, keep going. First up, an overview. • Installing software and loading data rarely worked perfectly and takes some time. Think…
I paused efforts on an introductory course on machine learning and statistical inference after finding Professor Matthew J. Salganik’s draft book, Bit by Bit: social research in the digital age, which has been available for open peer review since summer 2016 (click on the book title to access it, and here to learn about the…
Week one of the course introduced Apache Hadoop software, used for distributed processing of massive unstructured data, week two took us deeper into accessing and operating on big data and took me far, far away from my comfort zone. The least geeky explanations of Hadoop and MapReduce that I could find are here and here…
After social media analytics I signed up for this Big Data Analytics programme. Also by Queensland University of Technology, it is a series of four courses covering the collecting, storing and managing (week 1); statistical inference and machine learning (week 2); mathematical modelling (week 3) and data visualisation (week 4). (As an aside for anyone…
This post is a short detour from the Big Data path, and a brain dump of ways of working I find to be helpful when commissioning an evaluation, or responding to an ITT to deliver an evaluation (if you have ever asked me for advice then it will look familiar!). As I started to explore…
Following last week’s overview this post provides a bit more detail on the doing of social media analysis. This course ran for three weeks, each week focusing on a different aspect and using a different tool: understanding & gathering (TAGS), analysing (Tableau), and visualising with social network analysis(Gephi). As stated, the course does work for…