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Final Portfolio for Methods of Text Analysis

Instructor: Lisa Marie Rhody
Course: DHUM72500
Semester: Fall 2019
Date Due: 11:59 PM, Friday, December 20th

All students are required to submit a final portfolio. The portfolio should include a copy of all of your weekly assignments, and a 5 page, typed, position paper written for an academic audience with appropriate MLA or Chicago Manual Style and including appropriate citations. The final position paper will make a case for your position on the question: “Can there be a feminist text analysis?” It will draw from examples in the notebook assignments as well as secondary sources. Final portfolios can take a variety of formats, ranging from a combined PDF document to a web portfolio to a GitHub repository. We will discuss in more detail during the semester.

Course syllabus

How we got here

We began the semester with reading that explored the usual process of performing a computational text analysis task, and we’ve progressed through each “unit” of the course in the order in which one would be expected to do to create a computational text analysis project. The final assignment represents the culmination of that activity in an analytical position paper supported by regular hands-on work. 

During the course of the semester, you have been asked to do reading on three fronts: theoretical pieces on feminism, text, and analysis, scholarly projects that make use of methods of computational text analysis to pursue a humanistic question, and tutorials about how computational text analysis is performed. You’ve been asked to do assignments on a near weekly basis in which you are asked to learn technical / computational skills or engage with code that is important to know in order to perform computational text analysis. Sometimes this has taken the shape of completing assignments in DataCamp or another tutorial. Sometimes this has been taking a Jupyter notebook and running the code while engaging with it through written responses in markdown cells. 

Throughout, we have been deliberate, self-examining, and skeptical. As we’ve considered texts as documents, divided into enumerated segments, counted, labeled with features, and clustered, we’ve been also wondering aloud about what happens when we consider texts this way. Counting and empiricism is necessarily participant in a feminist project, especially one that might lead toward social justice as Sarah Ahmed encourages us. Still, what humanists value of texts is also their abstraction, metaphorical, figurative, and affective meanings, not to mention their social, sonic, and visual aspects. These discussions all lead us to the final class: a round table discussion in which we consider what it is we mean by “feminist text analysis” and what could / might / should be achieved by approaching texts this way. 

What comes next

The portfolio assignment is designed to connect your thinking across all of these projects and domains. The objective of the course is to position you so that you can make reasoned, evidence-based arguments about text analysis from a feminist perspective. You are asked to demonstrate in writing the connections we have made in class discussion between the practical and code-driven and the theoretical and cultural. 

Your portfolio should include the following: 

  1. Your name, contact information, and course number.
  2. A direct email to me to let me know how you are submitting your portfolio and how I can access it. Please also provide an email address where you can be reached over break. The email you send should have the following subject heading: <Your Name>: DHUM72500 FINAL PORTFOLIO. 
  3. A table of contents, which includes simply a list of the materials that are included in your portfolio with links to where to find them. 
  4. A five-page, typed, academic introduction, which uses conventional methods of citation based on a widely-used citation style (MLA, Chicago, etc). This paper takes a position about feminist text analysis. Does it exist? Could it exist? What does it look like? What would a speculative feminist text analysis include? Addressing any of those questions would be appropriate. You can also create your own. This document should draw from your code-based experience. How does/doesn’t your work with code support your argument. 
  5. A copy of the Jupyter notebooks you completed with interspersed reflections and comments about the code that connect the day’s reading with the text analysis method. While the code has mostly been written out for you, each notebook should include your own markdown cells that put the readings from the week in conversation with the code. **
  6. A list of the names of the lessons you completed from DataCamp. 

Methods of Submission

The following are possible methods of submission for your portfolio. If none of these suit you, please feel free to use another approach. Be sure, if you do, to explain how I can find the material and how I can access it if it is password protected. 

  • GitHub repository: You could send me a link to your personal GitHub repository. The Readme.md file should include links to each of the components in your portfolio. If your repository is private, you will grant me access to the repository by adding me to the repo (LMRHODY) or by providing me with a password. The 5 page paper could be uploaded as a Word Document, markdown file, or PDF. Don’t forget a bibliography / works cited.
  • Website: You could build a website to feature each of the parts of your portfolio. To do this, you might consider building a WordPress site on the CUNY Academic Commons with the 5 page introduction. There are plugins on the Commons that allow you to display markdown files and GitHub repos from your WordPress site. Be sure that you include a section for a bibliography / works cited. You might consider using this option if you want to make your paper linkable to examples or other conversations about text analysis elsewhere on the web. 
  • Dropbox folder: You could send me an invitation to share a Dropbox folder in which you have saved all of the contents of your portfolio. You would want to take special care if you use this option to make sure that I know where to find each of the elements of the portfolio. You could include sub folders with each of the weekly Jupyter notebooks, a page with the list of DataCamp lessons you completed, and the paper as either a PDF or .docx. 
  • Another option of your choosing, ranging from printing everything out into a PDF that you submit (this may not be a good option for those of you who are having trouble printing your Python notebooks to PDFs). 

Assessment

I will take the following into consideration while reviewing your portfolio: 

  • Did you send an email explaining where to find and how to access your portfolio? 
  • Can I find all of the parts of the portfolio easily based on what you have provided? 
  • Does the portfolio include all of the components listed above? 
  • Does your paper present your own argument, supported through a combination of code-based examples and secondary readings?
  • Do your notebook assignments demonstrate your attempts throughout the semester to a.) engage with the weekly topic (questions, data, conceptualization, operationalization, and analysis) b.) connect the readings to the code in some way and c.) try to learn something new.
  • Has class discussion impacted your work? 

Working together on portfolios is perfectly acceptable, even encouraged. Submitted  work should acknowledge collaborators. 5-page papers should demonstrate your own thoughts. 

[NOTE: There are 9 repositories and 10 notebooks currently in our GitHub course space. There is a maximum of 10 notebooks you can submit for credit during the semester, and a maximum of 4 DataCamp chapters. ]

You can email me with questions along the way at lrhody@gc.cuny.edu