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.
Important to note absences in research - in this case, that many letters were most likely lost or discarded due to "lack" or importance
Letters were the method by which people sought patronage, garnered favor, and engineered their social mobility;
Historian's Macroscope - Reciprocity in letters illustrates a social network.
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.
Could a material culture analysis of a commodity that was traded yield a network?
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.
Helps visualize scholarly relationships.
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.
which can make the findings clearer
We need to be extremely careful when analyzing networks not to read power relationships into data that may simply be imbalanced.
& note these absences. As Historians Macroscope stated earlier, Digital Historians should always specify the limits of their data analysis.
Following the entailogram over time reveals conflict and eventual resolution.
Networks can be used to show the growth of a specific topic and some of the key figures involved in its conception.
Besides this special case of two opposing colors, it is best to avoid using hue to represent quantitative data.
So many moving parts in crafting these ... do Digital Historians have the option to receive feedback on their visualizations? Do peer reviewers make comments regarding colors employed and/or choice of visualization?
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.
Visualizations present data in a readable way and they can drive home points more so than a text description.
Networks, blunt methods for considering connections,do not provide a way to reflect on the quality of
This study further stresses the importance of "knowing the history" of the subject matter you're researching. The author knew that Brown's Manifesto did not compare to more influential/ significant feminist manifestos. However, the large amount of mentions in Deepwell's anthology may lead someone who's less knowledgeable about this subject matter to make speculations regarding the importance of Manifesto for the Feminist Artist.
trans-generational and transnational exchange
Revealed through this textual analysis. Challenge preconceived ideas of feminist art.
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
Textual analysis further broadens Schneemann's social network. Thus, revealing her connections and influences.
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.
Hypothetically speaking, if you were to create a visualization... how would you identify a group like Poor Black Women' Study Group if they use different names?
I share this not to reveal my own sloppy data, but to highlight the difficulties of doing this kind of visualization.
Goes back to the importance of picking the right visualization that we discussed in class.
I appreciate how Digital History scholarship links you to website pages to gain more knowledge on a proposed topic
oth similarity in word usage and contrasts that reflected differences in social class, location, and time period.
Great use of a visualization.
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:
Human intervention coupled with the results of topic modeling.
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.
A starting point for research. Not the be-all, end-all. The historian shapes their topic model to fit the historical questions they are posing.
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
Word cloud has its benefits, but it is hard to see past the cons. I think these visualizations are only beneficial to an audience that has context.
The decision by Mario Gonzalez illustrates how individuals create their own life-narrative
Re-writing their own history, so the (alleged) "negative" parts are forgotten and erased.
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.
Which would lead to researchers policing themselves and questioning if their work would harm an individual and/or their descendants.
This study wanted to consider the period from a new perspective – that of the consumer. Of interest was:
The "hidden population" may have wanted to maintain their anonymity - or at least that's what the Mario Gonzalez case suggests.
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.
Much is lost when information is taken out of its initial context. I appreciate the Emilie Davis' diaries because it juxtaposes the diary page scans next to the transcriptions.
I adopt instead the more specific term, ‘digital archival environment’, to describe accessing online digitised surrogates of materials taken from archives.
Brick and mortar archives and digital archives need to abide by ethical standards. Relevant (alive) individuals and their descendants should be contacted before publishing this information on the internet.
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.
Is this a firm rule in the Digital History community or is it more of a suggestion?
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
Feminist Research Practices and Digital Archives stresses the importance of maintaining the trace of labor inherent in digitized items. Acker and Clement call for the trace of labor in data collection, to better comprehend the datafication of culture.
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
Interesting to see how the authors attribute so much agency to data. It further solidifies how humans shape, and are shaped by data.