Information Visualization & Distant Reading - Caden

Chapters 5 and 6, as well as the essays on multimodal analysis, data mining, information visualization, and distant reading have enabled me to see how Digital Humanities can take a vast quantity of information and make it easier to detect patterns. Distant reading is particularly interesting because rather than closely examining a single text, the researcher looks at a large number of texts and employs digital tools to identify patterns that would be difficult to spot on an individual basis. At the same time, the essay entitled Problems of Scale showed me that working with larger amounts of data does not necessarily lead to more accurate or significant results. In fact, the scale of the data can introduce new problems because researchers have to decide which information is important and how it should be presented.

This idea is very closely related to Six Degrees of Francis Bacon. The project involves the use of data mining and network visualization in order to reconstruct the relationships that existed among people in early modern Britain. Each individual is represented as a node, and the connections between them are shown as edges. In some cases, the relationships are statistically deduced, while in other cases they have been provided by people themselves. What interests me is that the visualization enables us to see the overall structure of a network which would be almost impossible to grasp by reading through the biographies of thousands of individuals. Yet the visualization also demands interpretation, since a line linking two people does not necessarily indicate the nature of their relationship, highlighting one of the limitations of converting complex historical information into data.

Yesterday, Today, Tomorrow is another example of distant reading and visualization. The project looked at hundreds of thousands of tweets relating to the COVID-19 pandemic and employed AI to arrange them according to emotions like fear, joy, sadness, and confidence. Rather than having to read the individual tweets, users are able to observe the larger emotional trends as they develop over time, and I believe this shows how visualization can make something abstract, such as collective emotion, more understandable.