8 – Historical Network Research

Network visualisations are increasingly common not only in the realm of the Digital Humanities but as means for data exploration and data illustration in general. In this session we will take another look at the #twitterstorians network and explore it using NodeXL, a visualisation software which is particularly useful for beginners. What lies behind the aesthetics of network visualisations? How can we represent complex social relations visually? How can we represent ambivalence, context knowledge and interpretation in a graph?

 — make sure you bring a laptop with WinXP (or higher) + Microsoft Office 2007 (or higher) + NodeXL installed —

Required Readings

 

 Recommended Reading

Tool of the day:

4 thoughts on “8 – Historical Network Research

  1. 1. Graphing tools are a very attractive way to provide a big picture. How do researchers work past the “sexy, wow-factor” and guide the public to interpreting data accurately? How reliable are the space/layout algorithms for representing various forms of historical data?

    2. Network analysis tools appear to require quantitative or tabular data in order to create a visualization. How are researchers finding ways to graph incomplete data or data that is subject to more than one form of interpretation?

    3. Are network analysis tools stratifying the academic field of history or uniting it? Will historical researchers need to become information professionals in order to have their research accepted into the field?

    4. Are there limitations to complexity? As with the example of airport hubs, how do we accommodate for the realistic applications of the data and not what the data appears to represent?

  2. 1. Scott Weingart warns that most network analysis tools are algorithmically geared towards the analysis of single mode networks, partially because those are the kind of networks that computer scientists deal with most often. Can historians and other scholars who are more interested in multi-modal graphs express their particular needs anywhere? Should they?

    2. Much of the material we read focused on the use of networks to analyze historical objects of study. Can networks (and the construction of them) be helpful to historians in other ways? One example I can think of is in information retrieval– if work is done to connect entities with each other, that information can be used to better search for and recall certain sources or entities, even if the underlying network eliminates real-world complexity too much to inform useful analysis.

    3. Marten’s paper presenting VennMaker advises that the tool is only meant to be used for small networks. Should historical inquiry into graphs focus more on smaller networks rather than larger ones? Is it too difficult to analyze the latter without ignoring interesting idiosyncrasies and nuances?

    4. If network analysis is used as part of a published historical work, should the author(s) be compelled to share their methodology for deriving it? This practice is common in the social sciences, but would probably be wildly out of place in historical scholarship as currently published. Further, should they share their data, to allow for things like reproducibility and peer review?

  3. 1. Network analysis provides us an opportunity to think how we normally sort out, categorize and interact different characters appear in historical materials. How does the process of conceptualizing edges and nodes for network analysis can be reflective to our traditional way of writing history?

    2. To what extent should historians know the background algorithm of network visualizations?

    3. From the posts and articles, I learned that many scholars are still struggling to define what network analysis can do. Like other digital history tools, scholars start using tools while lingering around the question of network analysis as a methodology, scholarship, or theory. What kinds of things should we be careful about to use network analysis in order to read materials in a way that could not have done before?

    4. How can network analysis and visualization contribute to reveal changes over time?
    How does network analysis deal with shifting moments in relationships?

  4. 1. Claire Lemercier raises a number of important questions about the use of network research analysis and the work of historians, namely whether or not we are constructing or reconstructing the networks that we see. In Marten’s work, we learned that individuals within distinct helper networks were not aware of their membership in such an organization or which figures were central to its connectivity. How useful then are networks in representing social relations?

    2. Many of the digital history tools we’ve discusses have been used not only as a means of analysis but also as a teaching tool and a mode of historical argument. It seems that network visualizations are most useful as a research tool for the analyst (dynamic filters, etc.), and yet, large scale project like the Republic of Letters use the logic of social networks as a pedagogical platform. Is this kind of work misleading, given our experiences in working with nodeXL and the issues raised by Lemercier?

    3. Given that history is a study of the diachronic, how might scholars use network analysis to think through the “temporality of ties”? The relationships between nodes and edges give the impression of static relationships that do not change or adapt to historical circumstances, i.e. deportations or arrests. How might we represent this change over time in our visualizations? Should we?

    4. Scott Weingart makes it clear in his last post that historians should understand the way that different programs work to visualize our datasets: we should understand the logic of different algorithms, the nature of directed or undirected networks, and perhaps most importantly, whether our tool was built for a bi-nodal or multi-nodal network. Should historians incorporate this material as theory for a lay audience into the historical texts that are written to accompany these visualizations?

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