Tim Hitchcock, another member of the ‘With Criminal Intent’ team, has described how online technologies can change the way we access archives. Instead of being forced to navigate the hierarchical structures that archives impose on records, which in turn tend to reflect the workings of the institutions that created the records, we can directly find the people whose lives were regulated, influenced, shaped or controlled by the policies of those institutions.

Instead of merely hearing ‘the institutional voice… in all its stentorian splendour’, he says, we can listen in to ‘the quieter tones uttered by the individual’.[8]

As one of the first of a ‘new style’ of museum online collections, launching several internet generations ago in 2006, the Powerhouse Museum’s collection database has been undergoing a rethink in recent times. Five years is a very long time on the web and not only has the landscape of online museum collections radically changed, but so to has the way researchers, including curators, use these online collections as part of their own research practices.

Digging through five years of data has revealed a number of key patterns in usage, which when combined with user research paints a very different picture of the value and usefulness of online collections.

A number of our Web Science students are doing work analyzing people’s use of Twitter, and the tools available for them to do so are rather limited since Twitter changed the terms of their service so that the functionality of TwapperKeeper and similar sites has been reduced. There are personal tools like NodeXL (a plugin for Microsoft Excel running under Windows) that do provide simple data capture from social networks, but a study will require long-term data collection over many months that is independent of reboots and power outages.

As I wrote here a couple of weeks ago, I’m playing around with a variety of clustering techniques to identify patterns in legal records from the early modern Spanish Empire. In this post, I will discuss the first of my training experiments using Normalized Compression Distance (NCD). I’ll look at what NCD is, some potential problems with the method, and then the results from using NCD to analyze the Criminales Series descriptions of the Archivo Nacional del Ecuador’s (ANE) Series Guide. For what it’s worth, this is a very easy and approachable method for measuring similarity between documents and requires almost no programming chops.

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Historians often hope that digitized texts will enable better, faster comparisons of groups of texts. Now that at least the 1grams on Bookworm are running pretty smoothly, I want to start to lay the groundwork for using corpus comparisons to look at words in a big digital library. For the algorithmically minded: this post should act as a somewhat idiosyncratic approach to Dunning’s Log-likelihood statistic. For the hermeneutically minded: this post should explain why you might need _any_ log-likelihood statistic.

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Paradox Number One:  Social media foments revolution, but a sudden removal of social media can increase mobilization and create even more unrest.

We can all stand witness to the ways in which social and news media can spread a movement within and across nations.  I know an Egyptian who claimed that her family and friends knew that the revolution was going to occur in the weeks and days before it actually happened.  How?  Just by the messages on social media and between individuals.  In a similar fashion, social media proposed and flamed the fires of the occupy wall street movement in the weeks before it emerged, grew, and took hold as a real story in mainstream media outlets.