A common vision of the future of digital humanities is that some of the techniques will become so widely used as to be practically absorbed into mainstream humanities methods. They will become so unremarkable as to not even deserve their special classification as digital. But there are also indications of an opposite trend, where the methods become part of a wider “discipline of the digital.”
There is something about the digital humanities community which makes it a particular pleasure to engage with. My experience of DH events has been of meeting people who are already respected in their own fields, but are not afraid to put themselves into what is, after all, the vulnerable position of learning something completely new.
Whenever I see another piece of research using social media data, I must admit I roll my eyes. Social media will only ever capture the voices of the urban young – the type of people who have less difficulty in getting their voices heard than the poor and relatively less educated rural population. The shorthand way I use to express this is “peasants don’t blog” and I fret about the future of the social sciences where funding and focus will increasingly leave out the voices of this already disenfranchised majority.
What’s not to love about a big Indonesian wedding? Free food, a bit of socialization, and the chance to pull on your best kebaya. But for Indonesia’s political and economic elites, they are much more than that...
Despite not having the numbers in Indonesia’s house of representatives, President Joko Widodo has been able to score victories. But as the national police and corruption commission battle shows, that could soon change.
Considering the enormity of the task it faces, the National Election Commission (KPU) and its associated bodies have, in the past, done a good job of administering national and regional elections. But with 478,685 polling stations due to return results in the next two weeks, their oversight capacities will be stretched.
Perhaps because its technical intricacies are so difficult to grasp for the lay-person, natural language processing (NLP) scholarship borrows some of its terminology from other fields: “signals”, “noise”, “gold standards” and “ground-truthing” to name but a few. Used to describe the process of evaluating results in NLP, the term “ground-truthing” implies something of its other meanings – a sort of reality check that what is being measured remotely is actually true – but does it do this in practice?