he vast majority of network analysis deals with incomplete networks in the real world, and any statistical treatment of biases has to make assumptions about the distribution of missing links or nodes.

Letters were the method by which people sought patronage, garnered favor, and engineered their social mobility;

Historians can draw a number of inferences from small world networks, including the time it might have taken for materials to circulate within and across communities, and the relative importance of individual actors in shaping the past.

When two articles reference a common third work in their bibliographies, they get an edge drawn between then; if those two articles share 10 references between them, the edge gets a stronger weight of 10. A bibliographic coupling network, then, connects articles that reference similar material, and provides a snapshot of a community of practice that emerges from the decisions authors make about whom to cite.

The results of a network study can be used as an illustration, a research aid, evidence, a narrative, a classification scheme, and a tool for navigation or understanding.

We need to be extremely careful when analyzing networks not to read power relationships into data that may simply be imbalanced.

Following the entailogram over time reveals conflict and eventual resolution.

Besides this special case of two opposing colors, it is best to avoid using hue to represent quantitative data.

While my description of the chart does describe the trends accurately, it does not convey the sheer magnitude of difference between earlier and later years as covered by dissertations, nor does it mention the sudden drop in dissertations covering periods after 1970.

Networks, blunt methods for considering connections,do not provide a way to reflect on the quality of

trans-generational and transnational exchange

For example, Correspondence Courseincludes no letters to or from Austrian performance artist and filmmaker, Valie Export, although the two artists met in 1970, but Export ismentioned several times by Schneemann.25

What we really want here of course is a visualization that combines all the things, but I’ve resisted creating one for now. The complex historical questions of who gets counted when we count in histories of women’s liberation exists because data reduces people’s lived experiences to columns on a spreadsheet.

I share this not to reveal my own sloppy data, but to highlight the difficulties of doing this kind of visualization.

oth similarity in word usage and contrasts that reflected differences in social class, location, and time period.

When its entry scores are aggregated into months of the year, it shows exactly what one would expect over the course of a typical year:

In fact there is a danger in using topic models as historical evidence; they are configurable and ambiguous enough that no matter what you are looking for, you just might find it.

word cloud. In brief, they are generated through the following process. First, a computer program takes a text and counts how frequent each word is. In many cases, it will normalize the text to some degree, or at least give the user options: if “racing” appears 80 times and “Racing

The decision by Mario Gonzalez illustrates how individuals create their own life-narrative

However, having the opportunity to build up a greater understanding of an individual’s lifestyle and their social networks brings with it ethical concerns. These concerns are increased by their involvement in a criminal activity. Disclosing the identity of a ‘forgotten’ individual and their connection to crime has the potential to cause harm. Therefore, careful thought is needed about how this evidence is presented when sharing research findings, and in this digital age this may not just be in the form of a printed academic journal.

This study wanted to consider the period from a new perspective – that of the consumer. Of interest was:

Graphic designers intricate two page spreads are chopped in half when digitisation occurs at the page level. Layouts that carefully juxtaposed articles, poems, and photographs on a page are eradicated when individual items are digitised as separate files. An artist’s delicate work loses nuances when contrast levels are set to prioritise text legibility.

I adopt instead the more specific term, ‘digital archival environment’, to describe accessing online digitised surrogates of materials taken from archives.

How can a researcher determine whether individuals who appear in a digital archival environment have consented to this and what controls should they look for to mitigate this increased exposure? Researchers can check for copyright information, investigate searchability settings, and look for procedures that enable individuals to have materials taken down.

Creators' agency over data that has been created, collected, and managed is thus central to understanding the datafication of culture. Indeed, calls for agency over our individual data footprints and practices of collection exist, but more methods for understanding how individuals are interpolated through sociomaterial practices of data collection as subjects are still needed.17

But we know that data is not just given, it is taken up by people and given forms, standards, names, putting it into relationships with cultural practices.4Data is not nature, waiting to be tamed; it is always already a cultural product.5