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I’ve been hoping to use my current work on the Mood Music project to test out GitHub Actions for continuous integration (CI). There are a few extra steps needed for the Django set up because of databases etc so this is a little guide to save my future self the pain of figuring it all out again.
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You can read an update about the Mood Music study on inferring wellbeing from Spotify here, on a guest blog post I wrote for the Jean Golding Institute.
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After spending 3 months on a Python project (see the COVID-19 community map here!) I’ve gone back to an R project that I started in 2019. After getting used to using Python there have been a few functions that I’ve really missed in R, so I’ve collected a few substitutes that I’ve found.
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While the pandemic has derailed a lot of plans we have had the opportunity to work on a project with Public Health Wales, developing a novel data visualisation platform that helps identify vulnerable communities in Wales.
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Really excited to share that we have won a seedcorn grant from the Jean Golding Insitute for Data Intensive Science to pursue an idea about how we can infer wellbeing from music listening behaviours.
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Given how much I love the start of the new academic year (recovering addiction to fresh stationary), I thought I’d do a post to mark the start of the ‘new year’ and the start of my second year of my PhD with the things I’ve been thinking about achieving this year…
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We’re excited to share that we won the JGI/ONS 2019 Data Challenge. Have a look at our entry here.
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Since starting in research I’ve learnt some home truths about reproducibility in science. Thanks some fantastic researchers (listed at the end) I’ve also been taught some amazing lessons about reproducibility, and how to do it. So much so that I can’t see why you would work any other way, which is itself testament to the power of educating a new generation of scientists with lessons learned.
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Writing this up a little late, but at the beginning of February I got to attend MQ’s Mental Health Science conference. It was a two-day conference with a huge range of speakers talking about all sorts of research related to mental health, and was my first conference!
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One of my PhD aims will be around analysing data from Tweets using machine learning/ NLP (natural language processing, not neuro-linguistic programming – social work problems).
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A journalist tweeted this week that Alexandria Ocasio-Cortez (AOC) said that algorithms, driven by math, are racist. Something about the way the tweet was written struck me as sceptical, and many people in tech seemed to feel the same way. A lot of tech-experienced people weighed in to defend AOC, because if you have an understanding of how algorithms are made, and the existence of systemic racism, then you’ll understand that she’s right.
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I’m publishing this on the blog in case anyone else has been facing the same problem as me and is unsure how to get around it!