In Stephen Ramsay and Geoffrey Rockwell’s, article Developing Things: Notes toward an Epistemology of Building in the Digital Humanities, both authors cover topics that deal with debates happening in the field of Digital Humanities. After reading this piece, there was one moment in particular that stuck out to me. They reference the fact that a book with a bibliography can surely qualify as a scholarly work, but raise the question of whether the creation of digital tools can qualify as scholarly work as well (Building in Digital Humanities). As someone who hopes to engage with the Digital Humanities in my professional life, this spoke to me personally. If I choose to work in a primarily computational space, can my work still be considered scholarly? This question is discussed at length, and Ramsay and Rockwell believe that there is currently no definitive answer. The engaging with software can be split into two segments in this sense. There is the building process and the implementation of the product (Building in Digital Humanities). I believe that Ramsay and Rockwell’s case that focusing more on the building aspect of software can detract from the scholarly aspect of a work. Take for example neural networks. Many programmers can build them to identify handwriting. But, how many of those could use their creation to interpret a historical figure’s letters while synthesizing contemporary context with their analysis to create a new theory about some past event or culture? I believe that this is what sets a digital humanist aside from other scholars, and agree with Ramsey and Rockwell that Digital Humanists are able to create scholarly software. This quote in particular speaks to me on this issue:  “If the quality of the interventions that occur as a result of building are as interesting as those that are typically established through writing, then that activity is, for all intents and purposes, scholarship” (Building in Digital Humanities).

Tom Elliot and Sean Gillies expound on the usage of Digital Geography throughout the humanities in their article Digital Geography and Classics. Mapping geography in texts has been around since the 1990’s, but advancements in computation have allowed for the field to take off recently (Digital Geography).  This allows for an additional way to help search and share texts across disciplines. Originally, people would usually search by creator, time, or topic. With more nuanced text analysis, accurate geographical data can be extracted, helping others access it.  One prime example of improvement in this interdisciplinary field is the Pleiades Project. The Pleiades tool can be used to continuously update and diversify data sets of mapped text (Digital Geography). This allows for the digitization of these resources, increasing their availability as well. Overall, this is an exciting way to help index and share texts, and I am interested to see how it develops. As a student, I see the impact of these types of projects directly. This type of search could help me when researching for a paper or other project, as well as provide access to the text.

The Urban Electoral Coalitions article analyzes data from a local election in Los Angeles, California to understand the local demographics in the age of immigration into California. They used geography to capture this data as populations of immigrants are continually changing as the influx of immigrants increases and decreases depending on the region of the world they’re coming from. The researchers utilized colorful mapping technology to represent the different urban coalitions present in the city. I found this information and methodology very interesting as they were following demographic changes through mapping. They were able to track increased enthusiasm from Latinos as the mayor candidate was also Latino and therefore resonated with that population. Immigration continually changes these coalitions in American cities but with proper mapping technology we can follow these and understand the data and dynamics much better. We can draw interesting connections to Maine and the immigration to Lewiston and Portland through elections noted by KL, “The diversity within Maine is varied and not great compared to a place like Los Angeles. The diversity within cities like Portland and Lewiston must be acknowledged as well when looking at the voters map of Maine.” I agree with them on the basis that this methodology is universal and is extremely relevant to Maine in terms of immigration affecting elections.

The article published by the Political Geography for today’s class on mapping discusses the relationships between the demographics in Los Angeles and the political trends in the various areas within that state.  The maps done to demonstrate these trends, however, do not effectively communicate this to the audience as some of them make use of percentages and not actual figures, some lack borders that distinguish the individual states and the color coding of one map made use of colors that were too close to each other.

This article based on electoral coalitions within times of change in population made me think a lot about maps, visualizations, based on politics and collections of votes. I have been keeping an eye on the race for US Congress race still occurring after almost a week between Bruce Poliquin and Jared Golden. Many maps, for example on The New York Times, miss represent the state of Maine. In the figure 1 below, it seems as though Poliquin, the republican, is in the lead. When you actually take a look at the percentage there is a 1% difference between the leading candidates. The sparse population in most of the ‘republican’ areas doesn’t not account for a large discrepancy of votes for Poliquin. This visualization must be read with acknowledgment, along with percentages backing up the variation in population. 

The author of “Urban Mapping” also makes an interesting point about the diversity of population, which is also talked about in the article. The diversity within Maine is varied and not great compared to a place like Los Angeles. The diversity within cities like Portland and Lewiston must be acknowledged as well when looking at the voters map of Maine.

In Jim Enote’s video about Counter Mapping, he explains that there are many different ways in which to think about maps. He differentiates the maps that are able to exude the physical locations of places, and maps that are able to effectively tell a story. He claims maps that contain cultural information or important ancestral aspects should exist in order to create a sense of community to those that read these types of maps. Although this is extremely creative, I feel as if maps have a sole purpose, and intertwining this kind of information and maps would produce something more along the lines of art. KS’s piece made me think about this idea when he says, “It felt more like a piece of art that told a story. I’m not sure that is the same purpose of satellite view on Google Maps.”

When programming effective pieces of software, one must always consider the idea of scale.  It may be  effective to code at a small scale in order to dissect the inner pieces of your script. When analyzing data or meta data, designing for a small scale will not be effective, as one can be working with up to millions of entries. This is a problem that Lauren Tilton, Taylor Arnold, and Courtney Rivard address in their piece Locating Place Names at Scale for the 2018 Digital Humanities Conference in Mexico City. They speak about this same challenge of scale in regards to extracting geo spatial data from meta data in order to better visualize the movement of peoples during the 20th century in the United States (Locating Place Names).  It is easier to extract this data through close reading, but this is not possible when using a large corpus.  They were able to solve this complex problem though analyzing the meta data of when people spoke about migration through their texts, collecting a list of new locations to visualize (IBID). It is interesting to see how they were able to use meta data, and a strong understanding of how to analyze it at scale in order to create a fuller and more accurate depiction of human flow.

Topic modeling is a method used by programmers to analyze a large number of documents or text files. The documents are first manipulated to fix possible errors and make it easier for the computer. For example, all words are lowercased, punctuation is removed, and the tense of all words may be changed to a single form. This removes possible human errors in capitalization,  punctuation, and other categories. Meeks and Weingart argue that current topic modeling methods haven’t yet been perfected and for this reason shouldn’t be used in analysis. But, I agree with HC when they say that they “don’t believe we should give up on the whole field just because they haven’t produced a perfect finished product yet,” as there are many things in the computer world which aren’t yet flawless. For example, many companies use artificial intelligence for different aspects of products and business. Although artificial intelligence is nowhere near perfected, it constantly produces useful results for companies and consumers.

I found the article Using Metadata to Find Paul Revere very intriguing and an interesting way to use data. The first thing that the reader might notice is the conversational tone of the writing, as pointed out by HR: “the author wrote it like a class lecture or tutorial.” This keeps the reader engaged and  holds the readers attention throughout the piece. The author looks at different organizations of the time and finds how Revere connects to the organizations as well as how the organizations connect to each other. The author uses visuals, showing connections and strength of connections between organizations based on number of shared members. The visuals are good, but could be better if the user was able to interact with the visuals and possibly even click on individuals or organizations and only see that specific entity’s connections. This use of metadata and networking could be used in present day to learn more about terrorists, their organizations, and how they all relate.

In “Urban electoral coalitions…” we are shown the shifting demographics of an increasingly diverse Los Angeles. Many districts have overwhelmingly different racial and ethnic make-ups, mostly due to immigration and internal migration. This leads to many different groups wanting to be represented in the cities’ politics, so various coalitions must be created to garner a majority of the democratic vote.

This phenomena isn’t unique to Los Angeles, because most Western cities have their elections take the same format, while also having many different groups wanting to be represented by one party. But the authors looked at L.A. because it is so densely populated and because of that, there is more data, which in turn makes it more accurate in its representation.

I find it very interesting that the study considered a district “Latino” if the population of the district was 50% Latino, but to be considered a “Democratic” district, a higher barrier, 52%, needed to be reached. I think that shows how liberal the city is, and that a district that is 51-49 Democratic isn’t really a “Democratic” district.

In RC’s “Counter Mapping Response” they explain how a map is more than a picture of the landscape. It is an emotional representation of the land and a people’s connection to it. I think mapping out voting blocs is similar because racial groups don’t always vote a certain way, but if there is a candidate that focuses on issues predominantly felt by one community, it makes sense that there would be overwhelming support from that demographic.