“Learning LaTeX – Why should you care?” Series Part 1: Common Objections against learning LaTeX

Since some common objections why some people think learning LaTeX is not worth it or why the oppose LaTeX generally came up again in the Twitter discussion surrounding the recent post LaTeX for Philosophers? Logic and other Shenannigans, I quickly wanted to discuss the three most common objections agains LaTeX (in my experience) and why I think they’re not necessarily valid. Let’s get straight to it! 1) The “I can’t both be a good [insert job title/area of expertise here] AND spend time learning to code” aka the “LaTeX is hard to learn” objection A common argument used against LaTeX, not only in the Humanities, is “I already need all my energy being good at my job and now you want me to learn a new technology to distract me from it?”, like expressed in the following Tweet. But it’s really an extremely common one.  The argument is interesting to me because you also had to learn how to use

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The question of questions: Am I ‘techie’ enough for (a) Digital Humanities (degree)?

For the last two years, I had the responsibility to mentor master’s degree students in the Digital Humanities or to advise those interested in a DH degree. Today I wanted to discuss the most frequently asked question and that is: “Am I ‘techie’ enough for (a) Digital Humanities (degree)?” and partly also “How much math is there in a DH degree?”. This is my Christmas present to you. I’m hoping to do something LaTeX-related again soon but LaTeX templates are currently a go-to relax thing for times when I really need relaxing. And feeling obliged to write about that takes the fun out of it for me at the moment, so sorry, yet another DH post for now. Let’s get straight to it. Part of this post consists of the text of an informational video I made in my responsibility as a mentor for the DH degree programm in Graz. You can watch the video instead, if you like. However,

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Where can I *actually learn* programming? (as DH and otherwise)

To my surprise, lots of people regularly ask me where I learned to program. I have lots of posts on the subject and even multiple categories on the blog concerning the topic but maybe they’re “too disguised” under obscure titles for willing learners to actually find them. So I decided to give you a short summary with the key takeaways of what I’ve written on the topic so far and the most important links – boths to my other detailled blogposts and also on the resoures I would recommend as of now. However, before the “short summary” of takeaways and suggestions for willing learners, let me start with a deep dive into the very personal side of the question “Where did you actually learn to program?”. Now where did I actually learn to code? To answer the question “Where did I actually learn to program?”, we need to talk about my journey first. And.. Well, in order to answer this

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I finally finished my own #100DaysofDH – Here’s the wisdom!

Like the title says, I finally finished my own #100DaysofDH challenge. And I haven’t kept my promise to you guys. I (think I) said I would continue blogging every second week but now I’ve left you hanging for a whole month! I’m so sorry. I will try to get back into a regular posting schedule (still reduced until the dissertation is done but I’ll try to at least post every once in a while). Anyways, as I’m nearing the end of my #100DaysofDH challenge (and having declared myself as the worst challenge founder ever in history), I’m starting to get philosophical and the wisdom is coming in. Since I couldn’t deprive you of that, here it comes. (It really isn’t that bad, actually!) Wisdom 1: Read error messages, it works! This one is kind of self-explanatory but once you’re in those long coding sessions, you sometimes forget to do the most obvious stuff. I just recently coded on some stuff

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Machine Learning for the Humanities: A very short introduction and a not-so-short reflection

Machine Learning is one of those hot topics at the moment. It’s even starting to become a really hot topic in the Humanities and, of course, also in the DH. But Humanities and Machine Learning are not the most obvious combination for many reasons. Tutorials on how to run machine learning algorithms on your data are starting to pop up in large quantities, even for the DH. But I find it problematic that they often just use those methods, just show you those few lines of code to type in and that’s it. Frameworks have made sure that ML algorithms are easy to use. They actually have a super-low entry level programming-wise thanks to all those libraries. But the actual thing about ML is that you need to understand it or it’s good for nothing. (Ok, I admit there are some uses which are pretty straightforward and don’t need to be fully understood by users, such as Deep Learning powered

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Easy and quick strategies to #scicomm your DH project

Your digital project is great, I’m sure of that – but does it even exist if nobody knows about it? Science communication is the answer to avoid this philosophical dilemma. In this short post, I wanted to share a list of quick-and-easy-to-implement ideas to add some science communication to your projects. This is just a short post to give you some ideas, not tutorials on how to do it. However, I am open to any tutorial requests you might have on the topics involved. As for the Twitter bot, there is a short post available already. So let’s get to it! Quick and easy strategies to #scicomm your DH project Create a better / thematic / facetted search interface. Maybe people aren’t using your data because the interface is not intuitive and they can’t find things or don’t know what to look for and where to look. This is the basic building block to build all the following things on.

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Create your Tweepy/AWS-powered Twitter bot in a day

This post wants to convince you to try out creating a Twitter bot using Python Tweepy and AmazonAWS Lambda because it’s easy and fun. Of course, you can use any other utilities but Tweepy and AWS Lambda are the ones I tried. This is not a full tutorial but I can make one if anyone is interested. Inspired by the #100DaysofDH challenge In this post, I will just give you some basic Twitter knowledge, links for what you need to know to get it done and a link to the github of my #100DaysofDH challenge for which I implemented such a bot. If you want more guidance, please let me know. Also, read the post on the challenge because I noted down some restrictions I realized the Twitter automation guidelines impose on bots as I went along. In my example, I think I’m in fact doing one or two things which you actually shouldn’t do (I think bots shouldn’t like

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Transdisciplinary crossovers into the DH – The Don’ts and what can go wrong

Dear friends, today I want to illustrate some trans-disciplinary crossovers (into the DH) gone wrong. In earlier posts, I have already explained some of the dos (Looking at data with the eyes of a Humanist: How to apply digital skills to your Humanities research questions and Formulating Research Questions For Using DH Methods and What are ‘real’ Digital Humanities and how to get started?), so I assume I have you covered in that area. This is all very happy and positive – but I think I also owe it to you guys to give you an honest opinion of where you probably fucked up. It always hurts to learn these things and it’s more butterflies and rainbow-sprinkles to list all the empowering things you can do. But there are some traps as well and we don’t want you to fall into them. And if you already have, at least now you’ll have the closure to understand why you maybe have gotten rejected

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Join the #100DaysofDH Challenge!

I have been following the #100DaysofCode community for a while now and thought that it was sad that there didn’t seem to be a connection with the DH community. 100 Days of Code is such a great project which is motivational for those willing to learn but also a great way to foster a community. So I thought, why not start #100DaysofDH and I did. Looking forward to your contributions! The main activity around this will be happening on Twitter (account is @100DaysofDH, hashtag #100DaysofDH) but there is also a minimalist github.io page: https://100daysofdh.github.io/  On the github, you can also find the current state of the Tweepy and AWS-powered bot. The story behind the creation of this challenge Before getting into the details of how the challenge works, let me share some thoughts that I had in mind for the adaption of the 100 days challenge to the DH (skip this part if you just want the rules which can

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Learning to program: Failing fast and error messages

Today I wanted to talk about error messages and why you should learn to love them. If your mission is to learn programming, they show you your weakness and tackling a weakness is always the fastest way to learn. This is why the whole discussion of fixing error messages quickly turns into a philosophical discussion of a way of life: Walking the  path of the Ninja requires you to fail fast, early on, and often. Let me tell you why… Should you care about error messages and warnings? Are they secret messages from the universe? Yes, they are. If you’ve never given a hoot about errors and warnings in your life, congratulations. I don’t either. That is, until the thing doesn’t compile anymore. I am at awe with respect for people who fix mistakes before they become a problem. But I’m not one of them. What does this mean, however, with regard to your attitude towards failure? It probably means

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News on the DH and Gender Equality

A few weeks ago, I posted The Computational Humanities and Toxic Masculinity? A (long) reflection   and didn’t know what reaction to expect. It would either be a shitstorm or get ignored, I assumed. It turns out, however, that the timing might have been just right, since I was contacted by the (informal) Turing Institute reading group – they wanted to discuss my blog post. I was honoured that they did and that I could participate. Here I wanted to share some new insights and reflection prompts this discussion has sparked for me. First things first: Thanks for everyone who participated! First of all, I was happy this discussion happened at all. That’s exactly the type of thing I had aimed for with the post, yet I was pretty surprised it actually happened. After all, you normally don’t always get you want. Maybe it’s that help will always be given at Hogwarts to those who ask for it. 😉 So anyway,

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Looking at data with the eyes of a Humanist: How to apply digital skills to your Humanities research questions

In my recent post on how to get started doing DH, I basically said that the essence of being DH is looking at data with the eyes of a Humanist and gave some tips on how to get started in just 10 days. However, it’s not that easy. Learning digital skills and the problem of skill transfer A problem I see a lot is that H people fail to transfer their newly won practical DH skills to their own research questions. They don’t know how to look at their own material as data. They don’t know how to leverage digital methods to help answer their own research questions. But if it isn’t compatible with their own research, they’ll never deepen their knowledge enough to actually profit from their DH skills. If you don’t use them, they are forgotten quickly. So how do you make this transfer which I think is, so far, being neglected as a skill which has to

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The Computational Humanities and Toxic Masculinity? A (long) reflection

Today, I want to talk about the Computational Humanities discussion from last year and finally say something with regard to the gender issues in it. I called this post ‘Toxic Masculinity?’ and maybe that’s provocative to you. But maybe it also correctly describes a situation which could come to pass in the DH – a discipline which considers itself so forward-thinking – if we don’t take lurking issues seriously. So this is my reaction. Some disclaimers and considerations I wanted to respond to this discussion when it originally came up. Then I didn’t dare  to post it because I was kind of afraid there would be a bad reaction, especially as the slightly-shitstorm-like situation was still fresh and I didn’t want to offend anyone. So I didn’t and now it’s all kind of too late and not up-to-date anymore. But since the general subject is still relevant to me, I decided to use this Corona situation to write up this

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Formulating Research Questions For Using DH Methods

In the feedback forms I did on the DH classes I have taught over the last years, I got one feedback I didn’t expect: People were extremely grateful I had practiced with them how to formulate valid research questions which, apparently, no one had ever (really) done with them before. I found that quite astonishing because the DH are all about methods and methods are like specizalized tools. You need to know what you can use them for. So here’s the crashcourse. The Hammer and the Nail I want to start off with an analogy. A hammer is a specialized but not an extremely specialized tool. You can use it for a range of tasks, however, not all tasks are going to work equally well. Some might work but would actually require a more specialized tool if you had one. You can really use the hammer on about anything and almost always, something is going to happen. For example, you

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