accidentally typed “1909” rather than “1990” for one of the books.

Visualizations can also lie, confuse, or otherwise misrepresent if used poorly.

And, of course, we can also do that for the links between the people, using our 254x254 “Person by Person” table. Here is what that looks like.

Notice again, I beg you, what we did there. We did not start with a “social networke” as you might ordinarily think of it, where individuals are connected to other individuals. We started with a list of memberships in various organizations. But now suddenly we do have a social networke of individuals, where a tie is defined by co-membership in an organization. This is a powerful trick.

(Harvard, you may recall, is what passes for a university in the Colonies. No matter.)

Rest assured that we only collected metadata on these people, and no actual conversations were recorded or meetings transcribed. All I know is whether someone was a member of an organization or not.

I will show how we can use this “metadata” to find key persons involved in terrorist groups operating within the Colonies at the present time. I shall also endeavour to show how these methods work in what might be called a relational manner.

“Mapping Texts”is a collaborative projectbetween the University of North Texas and Stanford University whose goal has been to develop a series of experimental new models for combining the possibilities of text-mining and geospatial analysis in order to enable researchers to develop better quantitative and qualitative methods for finding and analyzing meaningful language patterns embedded within massive collections of historical newspapers

Here’s a video of my findings:

xtual document as an ordered hierarchy, or tree, so that it can be explored with computational tools. Humanities scholars use XML to represent their documents because the tree model is convenient both as a logical

text inside second definition term (dfn) node end tag

be used without reference to the Web or the Internet. For example, one could write XSLT to generate a table of information from an XML document and copy and insert it into a Microsoft Word document for printing on paper—all without ever being connected to the Internet.

documents in other forms. (In that latter case, you’ll need to convert them to XML, which typically involves a mixture of auto-tagging, where you run some global search-and-replace operations to insert markup, and manual tagging.) Or you may create new documents entirely from scratch, where you are creating not just the markup, but also the data content. Whatever the source of your data: The first stage of a digital humanities project is document analysis, where you determine the hierarchical structure of the documents that you wi

The preceding is not well formed because it doesn’t have a single root element that contains everything else. To change it into well-formed XML, wrap the dairy and snack elements in a root element, such as shopping_list. The following also is not well formed: <paragraph>He responded emphatically in French: <emph><foreign language="french">oui</emph></foreign>!</paragraph> This example has a single root element (paragraph), but the emph and foreign elements inside the

y be tagged as a place element, along the lines of: <paragraph>The American writer Jack London never lived in <place>London</place>.</paragraph> An author might wish to create an index of place names for the document, or cause a map to appear when the reader mouses over a place name while reading, or make it possible to search for the string “London” when it refers to the place, b

XML does not cope as well with multiple simultaneous hierarchies as it does with single hierarchies.

If we simply pass the computer an indifferentiated stream of text, it will not be able to identify the beginning and end of the various structural subcomponents. Markup is the process of inserting information into our document (this is called tagging in the XML context) that will take the structure that humans recognize easily and make it accessible to a computer.

The beginning of every digital humanities project: Document analysis

The creation of electronic texts that can be used in primary humanities research that would be impossible (or so impractical as to be essentially impossible) to conduct without computational assistance. The use of existing computational tools to interrogate those texts and obtain original research results that would not be attainable without the tools. Where existing computational tools are not able to meet the research goals, the development of original computer systems and programs to meet the researcher’s needs.

Scientists who try to model the print record overa significant time span often make assumptions about continuity that huma-nists would recognize as confining.15On this topic, and many others, a rareopportunity is emerging for a genuinely productive exchange between sci-entific methodology and humanistic theory.

Using algorithms for discovery raises an interesting but unfamiliar set ofphilosophical questions.

I don’t mean to imply a causal connection between these changes (forone thing, there are many other topics in the model; these three don’tconstitute a closed system). The illustration is only meant to show how topicmodeling can generate suggestive leads

But some strategies are also able to revealevidence that challenges prior assumptions.

Full-textsearchmadethatkindoftopicridiculously easy to explore. If youcould associate a theme with a set of verbal tics, you could suddenly turn updozens of citations not mentioned in existing scholarship and discoversomething that was easy to call ‘‘a discourse.’’

The scholarly consequences ofsearch practices are difficult to assess, since scholars tend to suppressdescription of their own discovery process in published work.2

It’s a name for a large family of algorithms that humanists have been usingfor several decades to test hypotheses and sort documents by relevance totheir hypothesis.

In practice, a full-text search is often a Boolean fishing expedition fora set of documents that may or may not exist.

Indeed, I made an android-only game out of it

as simple as clicking a link what do we think will turn up everyone else’s footnotes?

This gives the reader a radically transparent view into the source material supporting the case Suri argues.

Had I been asked two years ago if my project could have served as a prototype or guinea pig for the digital publishing initiative UMP is leading I would have been glad to help shape the development and design for authors producing narrative-driven digital publications

These processes often leave the academic writer isolated.

What if someone “scoops” an idea before it can be published? And what if a publisher won’t publish articles whose data and sources are already so open and available?

The result is a vast repository of knowledge and thought hidden from public view, a black hole’s worth of historical “dark data.”

Much like the stepped licenses that authors can choose from the Creative Commons, these badges encourage scientists to be more open about their research even if they cannot make their entire notebooks immediately “open source.”

In most cases, though, open source software (OSS) is code that anyone can inspect and change even while the software is in active development. It’s software that encourages collaboration and sharing at the earliest stages of a project’s life.

This is the goal of the macroscope: to highlight immediately what often requires careful thought and calculation, sometimes more than is possible for a single person

Microhistory involves the rigorous and in-depth study of a single story or moment in history, whereas macrohistory susses out long-term trends and eddies,

good historians, like good detectives, test their merit through expansion: the ability to extract complex knowledge from the smallest crumbs of evidence that history has left behind.

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