Assignments
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City of Albany Census Data, 1850 to 1940
The Census records dataset contains information on sex, age, race, birthplace, mother’s and father’s birthplace, literacy, occupation, and relationship between a person and the head of household if one exists. The US Census Bureau categorizes all people who are not in housing units as living in group quarters. Examples of group quarters include prisons, missions, and college housing. If a person on the census is not part of a household, their group quarter is listed. Information for these are the type, funding, and details of the group quarter.
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Intro to Text Analysis
Due: Tuesday March 12
Approx. 300-500 words and 3 embedded visualizations.
Select a set of 4-6 terms to investigate (hint: use the major words that appear in the Cirrus wordcloud to identify prominent terms and your knowledge of 19th century slave narratives to make productive associations). Using one of the visualizations covered in this lesson (Trends, Bubblines, Cirrus, and Links) and the two additional tools not covered in the lesson (Loom, Streamgraph, Knots, Microsearch, Scatterplot, and Mandala), brieflydescribe how your terms appear in each of your visualizations.
What are some additional questions that your visualizations provoke which might be investigated further through close reading?
You may optionally get started on the Intro to Topic Modeling slides, but we’ll cover these in class if you don’t get to them.
You may optionally complete this assignment in teams of up to three. If you complete this assignment as a team, each team member needs to complete the team evaluation form separately.
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Networks 1: Reupload
As you add more years the number of nodes and connections increase dramatically. You can see how each person interacts with those around them. Elizabeth Wemp and Isaac Wemp are two of the nodes which receive a considerable amount of ‘in degree’. Anna Clement and Abraham Canostens Peterse are two more who bridge the connections of the smaller nodes into the larger network.
Two of the major nodes when sizing by betweenness are Ezras Teganderasse and Anna Clement. These two appear to be the main nodes bridging the gap between the two halves. While Anna remains one of the largest nodes when filtering by degree, Ezra, while continuing to stay important, sees his size decrease.
When we go ahead and cluster, Anna is the largest contributor with 19%. Ezras, while still holding strong, is now absorbed into the much larger network of Aron Oseragighte at 16%. If the option of clustering had not been presented to me, I would never have attributed Seth Sietstarare Karihoge or Cornelius Bownen to having large networks. This method of clustering makes it much easier to see all the different connections.
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Introduction to Networks: Church Congregation 1735-46
In the first few years, the groups of the congregation do not seem to interact much, until 1738. The more years that are added up until 1745, the larger that the networks grow (unsurprisingly). This demonstrates that the congregation is expanding with time. This growth can be explained as either a growth in the size and interactions of the community as a whole or the church in particular. Either way, this growth is possibly demonstrating a time of peace or expansion. Before the data is seriously manipulated, John Wemp and Mary Butler appear to be the biggest nodes.
However, upon examination (with more colors added in), other connective nodes are apparent. Filtering by betweenness seems to decrease the size of nodes, as compared to filtering by year. By comparison, cluster comparisons were closer to the look of the by year filtering.
Anna Clement seemed to play a large role in connecting the two subgroups of the church together when the data is viewed by clustering as opposed to the role played by Aron Oseragighte and Cornelius Thanighwanege on the by year view. Other figures who play a larger role as explored on the clustering tab are Peter Young, Isaac Wemp, Abraham Canostens Peterse, and Cornelius Brown.
The various view point and manners of data organization allow for examinations of inter-personal relationships. The clustering and other views, allow researchers to view groupings that might not be readily apparent in more traditional forms of research scholarship.
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Final Project Guidelines
Your final project should be quantitative, argument-driven and interactive. The details are up to you. A project which is more heavily qualitative might only have one or two interactive visual elements; a heavily interactive project might have less essay text.
At a minimum, your project proposal should identify the dataset/s you’ll be working with, your team, and your goals. Your proposal must include:
- a data critique
- an outline of data cleaning you anticipate might be necessary
- a brief secondary bibliography of other works related to your data
- an outline of possible research questions or anticipated argument (think grant proposal)
- an outline of goals for possible data visualizations and reader interactions
- an outline of each persons’ responsibilities and roles if proposing a team project
- a timeline of project milestones, in addition to the April 9 wireframe due date and May 16 final due date
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Transcriptions
Due: Tuesday, February 19
For this assignment, we’re working in partnership with the Albany County Hall of Records and the new Albany Firefighter’s Museum. Our work for this assignment does an important service for the AFM and for ACHOR by doing the first necessary step of preparing their records for genealogists and future researchers to search and use. This assignment also gives us an up close and personal look at the painful process of data creation and the many questions of historical interpretation it opens up.
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Basic HTML & CSS Assignment
Due: Thursday January 31
For this assignment, you will need a text editor. I recommend Atom, Sublime Text, or Komodo Edit (not Komodo IDE). These are all free and easy to download. Do not try to do this assignment in Word, Google Docs or other wordprocessing programs. Word processors add extra formatting information that will mess things up. Text programs like Notepad and TextEdit should also be avoided.
