CS 467

Visualizing social interaction in networked spaces: investigation of patterns in networked communications systems such as messaging (email, instant messaging), social networking sites and collaborative sites; social network theory and visualizations; exploration of how to move beyond existing visualization techniques; visualizing the network identity over compilations of online data. Course Information: 3 undergraduate hours. 3 or 4 graduate hours. Prerequisite: CS 225.

Recommended but not required (I provide material from them in class):

1. Envisioning Information by Edward R. Tufte
2. Visual Explanations: Images and Quantities, Evidence and Narrative by Edward R. Tufte
3. The Visual Display of Quantitative Information by Edward R. Tufte
4. The Elements of Typographic Style by Bringhurst
5. Visualizing Data by William S. Cleveland
6. Design for Information by Isabel Meirelles
7. Information Visualization: Perception for Design by Colin Ware

Operationalize deductive and inductive reasoning - how does the visualization fit in this context (1)(2)(6)
Motivate a problem to attack via visualization - frame a good questions - understanding your audience (1)(2)(3)(6)
Parse, clean data in preparation for a visualization (1)(2)(6)
Perform sampling and basic statistical methods (2)(6)
Become proficient in basic visualization techniques, perception (2)(6)
Learn about abstraction, design, color theory (2)(6)
Programming skills for transitions in interactive visualizations (1)(2)(6)
Simple machine learning toolkits and techniques (1)(2)(6)
Evaluating visualizations (1)(6)
Implications, ethics and privacy in visualization (4)(6)
Group communication - problem solving, work allocation, peer review (3)(4)(5)
Critical Thinking: Critique research papers, critique colleagues and personal work. (1)(3)(6)
Learning to storyboard a design (1)(3)
Presenting work in a large audience/write about your work in a paper of publishable quality/ web pages about your work (3)(4)

Basic Visualization Techniques - Overviews, detail
Visualization Toolkits
Navigation - zooming, moving about a visualization
Narration and Storytelling with Vis
Cleaning/scrubbing Data
Abstraction and Data
Visualizing Uncertainty
Visualizing Text/Text analysis/simple data mining
Visualizing Audio/Audio analysis
Visualizing Video/Video analysis
Ethics and Privacy in the context of visualization
Design principles, typography
Color Theory - basics
Sociograms/social network analysis basics
Visualization for handhelds
Identity and visualization
Maps and visualization
Quantified self and identity

Revisions in last 6 years	Approximately when revision was done	Reason for revision	Data or documentation available?
Added material on simple machine learning for text and sentiment	Spring 2012	Many students wanted to incorporate elements of learning, but had not taken a machine learning class yet.	discussion in one lecture. Provided code in weka and python. Help in office hours
Added more material on visualization and storytelling.	Spring 2012	This was inspired by the growth of the NYT vis labs and the impact they've had on visualization.	Lecture discussion and presentations of NYT visualization, research papers on vis and storytelling
Visualization web toolkits	Spring 2012	This material is very relevant to visualization. Such toolkits did not exist when I began teaching this course as a 498	Lecture

Selected Elective.

2/14/2019by Karrie Karahalios