a.y. 2023/20SULLABUS
SYLLABUS
-
Introduction
Discussion
Projects to examine and discuss in class:
CLASS 1
October 16, 2024
Lecture
- The “Digital” of Digital Humanities
- What is Digital Humanities? Can it be defined?
Discussion
The history of digital Humanities (what is Digital Humanities? part II.)
We will discuss the following essay:
and confront it with (optional readings):
- Melissa Terras, and Julianne Nyhan. Father Busa’s Female Punch Card Operatives, in “Debates in the Digital Humanities”, edited by Matthew Gold and Lauren Klein (Ann Arbor, Minn.: University of Minnesota Press, 2016).
- William G. Thomas, Computing and the Historical Imagination, in “Companion to Digital Humanities”. The essay discusses “The Valley of Shadows”, examined in the previous class.
CLASS 2
October 22, 2024
In-class exercise
You will learn to manipulate and refine a simple dataset.
- OpenRefine, and BREVE
How is it made?
We will examine the following digital projects:
How is it made?
We will examine the following datasets:
CLASS 3
October 23, 2024
Lecture
- What is ‘data’?
- Forms of data and data-sets
- Data cleaning and manipulation
Discussion
How to present Data. Data Analysis.
We will discuss the following article:
- Christopher Groskopf, The Quartz guide to bad data, in “Quartz”, December 15, 2015.
- Katie Rawson and Trevor Muñoz, Against Cleaning, in “Curating Menus”, July 6, 2016.
Optional reading:
CLASS 4
October 29, 2024
How is it made?
We will examine how the following digital projects are made:
Discussion
Reconsidering data manipulation. Missing data.
We will discuss the following articles:
- Mimi Onuoha, Where We Live and How We Die: What a year of death looks like around the world, in “How We Get To Next”, June 30, 2016 (take a look also to Mimi Onuoha, On Missing Datasets).
Optional readings:
- Introduction and a chapter of Catherine Ignazio and Lauren Klein, Data Feminism (MIT press, digital book).
CLASS 5
October 30, 2024
Lecture
Data visualization: history, methods, and tools
CLASS 6
November 5, 2024
In-class exercise
You will start to use some data visualization tools.
- Please download Tableau public before class (for free, but it’s not open source).
- If you prefer something different, take a look at Apache Superset. It is an open-source data exploration and visualization platform. It may require a little more time and skill compared to Tableau, but it can be a rewarding experiment.
- If you can already code, you can opt for P5.
Discussion
Data visualization
We will discuss the following articles:
- Stéfan Sinclair, Stan Ruecker, and Milena Radzikowska, Information Visualization for Humanities Scholars, in “Literary Studies in the Digital Age: An Evolving Anthology” – The Modern Language Association of America. [⚠︎ Please be aware that inside this essay, there are links to projects that have been discontinued. These links could potentially direct you to unsafe websites].
- W. E. B. Du Bois’ Hand-Drawn Infographics of African-American Life (1900).
- Zachary Petit, One Design Firm’s Quarantine, in Data.
Optional content:
🎥 David McCandless, The beauty of data visualization (TED talk).
CLASS 7
November 6, 2024
How is it made?
We will examine the following DH projects:
Lecture
Text analysis and topic modeling; possibilities and drawbacks.
Algorithms of textual analysis.CLASS 8
November 12, 2024
Discussion
Data visualization, pt. II
We will discuss the following articles:
- Johanna Drucker, Humanities Approaches to Graphical Display, in “Digital Humanities Quarterly” 5 (2011).
- Giorgia Lupi, Data Humanism: The Revolutionary Future of Data Visualization.
Optional Readings:
- Steven Braun, Critically engaging with data visualization through an information literacy framework, in “Digital Humanities Quarterly” 18 (2018).
- Georgia Panagiotidou et al., Communicating Uncertainty in Digital Humanities Visualization Research, in “IEEE Transactions on Visualization and Computer Graphics”.
- Johanna Drucker, Graphesis: Visual Forms of Knowledge Production (Harvard University Press, 2014).
How is it made?
We will examine and reverse-engineering the following DH projects:
Discussion
Text analysis
We will discuss the following article:
- Nan Z. Da, The Computational Case against Computational Literary Studies, in “Critical Inquiry” 45, 2019. Consider also the debate in this forum.
Optional readings:
- Stephen Marche, Literature Is not Data: Against Digital Humanities, in “LARB” October 28, 2012.
- Markus Moessner et al., Analyzing big data in social media: Text and network analyses of an eating disorder forum, in “International Journal of Eating Disorders” 51 (2018).
- Maxime Bérubé et al., Social media forensics applied to assessment of post–critical incident social reaction: The case of the 2017 Manchester Arena terrorist attack, in “Forensic Science International” 313 (2020).
CLASS 9
November 13, 2024
In-class exercise
You will start to practice with text analysis tools.
Lecture
- Introduction to HTML and CSS.
- Concepts of Web Design.
- How to build a webpage from scratch
CLASS 10
November 19, 2024
In-class exercise
In this class segment, we’ll embark on a series of interconnected tutorials. You will start practicing with HTML and CSS to forge a simple page.
Optional readings:
HTML Handouts and the Web Content Accessibility Guidelines (WCAG) 2.1.
Lecture
- Infographic: A History of Data Graphics
We will also examine:
CLASS 11
November 20, 2024
Optional reading:
Discussion
We will discuss the following materials:
- The first chapter of: Jonathan Crary, Techniques of the Observer: On Vision and Modernity in the Nineteenth Century (Boston: MIT Press, 1990).
- Anne Burdick, Meta! Meta! Meta!: A Speculative Design Brief for the Digital Humanities, in “Visible Language” 49 (December 1, 2015).
How is it made?
We will examine the following DH project:
Midterm Written Test
Lecture
- Digital maps
- GIS and digital gazetteers
CLASS 12
November 26, 2024
MIDTERM WRITTEN TEST
In-class exercise
In this class segment, you will build a digital map with QGIS
Discussion
Digital maps
We will discuss the following articles/publications:
- Rhiannon Firth, Critical Cartography, in “The Occupied Times” April 23, 2015.
- David Turnbull, Maps Are Territories: Science Is an Atlas: A Portfolio of Exhibits (Chicago: University of Chicago Press, 1993)
Optional Readings:
- Sarah Battersby et al., Implications of Web Mercator and Its Use in Online Mapping, in “Cartographica: The International Journal for Geographic Information and Geovisualization” 49 (2014), pp. 85–101.
- Charles Travis and Alexander von Lünen (eds.), “The Digital Arts and Humanities: Neogeography, Social Media and Big Data Integrations and Applications” (Springer, 2015), pp. 153–167
CLASS 13
November 27, 2024
How is it made?
We will examine the following DH projects:
In-class exercise
In this section, participants can work together and bring up any concerns related to their current digital projects. We’ll briefly go over the state of their work and address any technical or conceptual difficulties that may have encountered.
Lecture
Introduction to AI: From the first models to machine learning.
How is it made?
We will examine the following DH projects:
CLASS 14
December 2024
Lecture
- Deep machine learning
- An introduction to artificial neural networks
CLASS 15
December 2024
Discussion
We will discuss the following articles:
- Stephen Wolfram, What Is ChatGPT Doing … and Why Does It Work? (February 14, 2023)
- J. McCarthy, M. L. Minsky et. al., A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence (1955).
- Cade Metz, What Exactly are the dangers of AI?, in “The New York Times” (May 1, 2023).
Optional Readings:
Lecture
An introduction to classical network analysis.
Discussion
We will discuss the following articles:
- Scott Weingart, Demystifying Networks, Parts I & II, in “Journal of Digital Humanities” 1 (Winter 2011).
- Mushon Zer-Aviv, If Everything Is a Network, Nothing Is a Network, in ”Visualizing Information for Advocacy”, January 8, 2016.
How is it made?
We will examine the following DH projects:
CLASS 16
December 2024
In-class exercise
The participants will work on their projects and refine them for the upcoming presentation.
In this section, participants can work together and bring up any concerns related to their current digital projects. We’ll briefly go over the state of their work and address any technical or conceptual difficulties that may have encountered.
CLASS 17
December 2024
CLASS 1
October 16, 2024
Introduction
Discussion
Projects to examine and discuss in class:
- The Battle of Hong Kong – 1941
- The Valley of Shadows
- The Little Giddings Harmonies
- http://learnpalestine.politics.ox.ac.uk/ (description of the project here)
- The Software That Shapes Workers’ Lives
Lecture
- The “Digital” of Digital Humanities
- What is Digital Humanities? Can it even be defined?
CLASS 2
October 22, 2024
Discussion
The history of digital Humanities (what is Digital Humanities? part II.)
We will discuss the following essay:
and confront it with (optional readings):
- Melissa Terras, and Julianne Nyhan. Father Busa’s Female Punch Card Operatives, in “Debates in the Digital Humanities”, edited by Matthew Gold and Lauren Klein (Ann Arbor, Minn.: University of Minnesota Press, 2016).
- William G. Thomas, Computing and the Historical Imagination, in “Companion to Digital Humanities”. The essay discusses “The Valley of Shadows”, examined in the previous class.
In-class exercise
You will learn to manipulate and refine a simple dataset.
- OpenRefine, and BREVE
How is it made?
We will examine the following digital projects:
CLASS 3
October 23, 2024
How is it made?
We will examine the following datasets:
Lecture
- What is ‘data’?
- Forms of data and data-sets
- Data cleaning and manipulation
CLASS 4
October 29, 2024
Discussion
How to present Data. Data Analysis.
We will discuss the following article:
- Christopher Groskopf, The Quartz guide to bad data, in “Quartz”, December 15, 2015.
- Katie Rawson and Trevor Muñoz, Against Cleaning, in “Curating Menus”, July 6, 2016.
Optional reading:
How is it made?
We will examine how the following digital projects are made:
CLASS 5
October 30, 2024
Discussion
Reconsidering data manipulation. Missing data.
We will discuss the following articles:
- Mimi Onuoha, Where We Live and How We Die: What a year of death looks like around the world, in “How We Get To Next”, June 30, 2016 (take a look also to Mimi Onuoha, On Missing Datasets).
Optional readings:
- Introduction and a chapter of Catherine Ignazio and Lauren Klein, Data Feminism (MIT press, digital book).
CLASS 6
November 5, 2024
Lecture
Data visualization: history, methods, and tools
In-class exercise
You will start to use some data visualization tools.
- Please download Tableau public before class (for free, but it’s not open source).
- If you prefer something different, take a look at Apache Superset. It is an open-source data exploration and visualization platform. It may require a little more time and skill compared to Tableau, but it can be a rewarding experiment.
- If you can already code, you can opt for P5.
CLASS 7
November 6, 2024
Discussion
Data visualization
We will discuss the following articles:
- Stéfan Sinclair, Stan Ruecker, and Milena Radzikowska, Information Visualization for Humanities Scholars, in “Literary Studies in the Digital Age: An Evolving Anthology” – The Modern Language Association of America. [⚠︎ Please be aware that inside this essay, there are links to projects that have been discontinued. These links could potentially direct you to unsafe websites].
- W. E. B. Du Bois’ Hand-Drawn Infographics of African-American Life (1900).
- Zachary Petit, One Design Firm’s Quarantine, in Data.
Optional content:
🎥 David McCandless, The beauty of data visualization (TED talk).
How is it made?
We will examine the following DH projects:
CLASS 8
November 12, 2024
Lecture
Text analysis and topic modeling; possibilities and drawbacks.
Algorithms of textual analysis.Discussion
Data visualization, pt. II
We will discuss the following article:
- Johanna Drucker, Humanities Approaches to Graphical Display, in “Digital Humanities Quarterly” 5 (2011).
- Giorgia Lupi, Data Humanism: The Revolutionary Future of Data Visualization.
Optional Readings:
- Steven Braun, Critically engaging with data visualization through an information literacy framework, in “Digital Humanities Quarterly” 18 (2018).
- Georgia Panagiotidou et al., Communicating Uncertainty in Digital Humanities Visualization Research, in “IEEE Transactions on Visualization and Computer Graphics”.
- Johanna Drucker, Graphesis: Visual Forms of Knowledge Production (Harvard University Press, 2014).
How is it made?
We will examine and reverse-engineering the following DH projects:
CLASS 9
November 13, 2024
Discussion
Text analysis
We will discuss the following article:
- Nan Z. Da, The Computational Case against Computational Literary Studies, in “Critical Inquiry” 45, 2019. Consider also the debate in this forum.
Optional readings:
- Stephen Marche, Literature Is not Data: Against Digital Humanities, in “LARB” October 28, 2012.
- Markus Moessner et al., Analyzing big data in social media: Text and network analyses of an eating disorder forum, in “International Journal of Eating Disorders” 51 (2018).
- Maxime Bérubé et al., Social media forensics applied to assessment of post–critical incident social reaction: The case of the 2017 Manchester Arena terrorist attack, in “Forensic Science International” 313 (2020).
In-class exercise
You will start to practice with text analysis tools.
CLASS 10
November 19, 2024
Lecture
- Introduction to HTML and CSS
- Concepts of Web Design
- How to build a webpage from scratch
In-class exercise
In this class segment, we’ll embark on a series of interconnected tutorials. You will start practicing with HTML and CSS to forge a simple page.
Optional readings:
HTML Handouts and the Web Content Accessibility Guidelines (WCAG) 2.1.
CLASS 11
November 20, 2024
Lecture
Infographic: A History of Data Graphics
We will also examine:
Optional reading:
Discussion
We will discuss the following materials:
- The first chapter of: Jonathan Crary, Techniques of the Observer: On Vision and Modernity in the Nineteenth Century (Boston: MIT Press, 1990).
- Anne Burdick, Meta! Meta! Meta!: A Speculative Design Brief for the Digital Humanities, in “Visible Language” 49 (December 1, 2015).
How is it made?
We will examine the following DH project:
CLASS 12
November 26, 2024
MIDTERM WRITTEN TEST
Lecture
- Digital maps
- GIS and Digital gazetteers
In-class exercise
In this class segment, you will build a digital map with QGIS
CLASS 13
November 27, 2024
Discussion
Digital maps
We will discuss the following articles:
- Rhiannon Firth, Critical Cartography, in “The Occupied Times” April 23, 2015.
- David Turnbull, Maps Are Territories: Science Is an Atlas: A Portfolio of Exhibits (Chicago: University of Chicago Press, 1993).
Optional Readings:
- Sarah Battersby et al., Implications of Web Mercator and Its Use in Online Mapping, in “Cartographica: The International Journal for Geographic Information and Geovisualization” 49 (2014), pp. 85–101.
- Charles Travis and Alexander von Lünen (eds.), “The Digital Arts and Humanities: Neogeography, Social Media and Big Data Integrations and Applications” (Springer, 2015), pp. 153–167
How is it made?
We will examine the following DH projects:
CLASS 14
December 2024
Lecture
Introduction to AI: From the first models to machine learning.
In-class exercise
In this section, participants can work together and bring up any concerns related to their current digital projects. We’ll briefly go over the state of their work and address any technical or conceptual difficulties that may have encountered.
How is it made?
We will examine the following DH projects:
CLASS 15
December 2024
Lecture
- Deep machine learning
- An introduction to artificial neural networks
Discussion
We will discuss the following articles:
- Stephen Wolfram, What Is ChatGPT Doing … and Why Does It Work? (February 14, 2023)
- J. McCarthy, M. L. Minsky et. al., A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence (1955).
- Cade Metz, What Exactly are the dangers of AI?, in “The New York Times” (May 1, 2023).
Optional Readings:
CLASS 16
December 2024
Lecture
An introduction to classical network analysis.
Discussion
We will discuss the following articles:
- Scott Weingart, Demystifying Networks, Parts I & II, in “Journal of Digital Humanities” 1 (Winter 2011).
- Mushon Zer-Aviv, If Everything Is a Network, Nothing Is a Network, in ”Visualizing Information for Advocacy”, January 8, 2016.
How is it made?
We will examine the following DH projects:
CLASS 17
December 2024
In-class exercise
The participants will work on their projects and refine them for the upcoming presentation.
In this section, participants can work together and bring up any concerns related to their current digital projects. We’ll briefly go over the state of their work and address any technical or conceptual difficulties that may have encountered.